{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FSRS4Anki Optimizer Post-Lapse Stability Offset\n",
    "\n",
    "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/main/archive/candidate/post-lapse_stability_offset.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here are some settings that you need to replace before running this optimizer.\n",
    "\n",
    "filename = \"../collection-2022-09-18@13-21-58.colpkg\"\n",
    "# If you upload deck file, replace it with your deck filename. E.g., ALL__Learning.apkg\n",
    "# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
    "\n",
    "# Replace it with your timezone. I'm in China, so I use Asia/Shanghai.\n",
    "# You can find your timezone here: https://gist.github.com/heyalexej/8bf688fd67d7199be4a1682b3eec7568\n",
    "timezone = 'Asia/Shanghai'\n",
    "\n",
    "# Replace it with your Anki's setting in Preferences -> Scheduling.\n",
    "next_day_starts_at = 4\n",
    "\n",
    "# Replace it if you don't want the optimizer to use the review logs before a specific date.\n",
    "revlog_start_date = \"2006-10-05\"\n",
    "\n",
    "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n",
    "filter_out_suspended_cards = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import sqlite3\n",
    "import time\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import math\n",
    "from typing import List, Optional\n",
    "from datetime import timedelta, datetime\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch import Tensor\n",
    "from torch.utils.data import Dataset, DataLoader, Sampler\n",
    "from torch.nn.utils.rnn import pad_sequence, pack_padded_sequence, pad_packed_sequence\n",
    "from sklearn.model_selection import StratifiedGroupKFold\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from itertools import accumulate\n",
    "from tqdm.auto import tqdm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deck file extracted successfully!\n",
      "revlog.csv saved.\n",
      "Trainset saved.\n",
      "Retention calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "850842a361474058be869a1a2a61d98f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/26286 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stability calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3c757531031c4bdcbae8368d2d8d356c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "analysis:   0%|          | 0/489 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis saved!\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "      r_history  avg_interval  avg_retention  stability  factor  group_cnt\n",
      "              1           1.1          0.892        1.0     inf       2063\n",
      "            1,3           3.1          0.920        4.0    4.00       1600\n",
      "          1,3,3           7.1          0.910        7.9    1.98       1320\n",
      "        1,3,3,3          16.6          0.862       10.8    1.37        986\n",
      "      1,3,3,3,3          36.5          0.840       22.3    2.06        659\n",
      "    1,3,3,3,3,3          77.0          0.861       36.4    1.63        358\n",
      "  1,3,3,3,3,3,3         117.9          0.906       38.5    1.06        177\n",
      "              2           1.0          0.902        1.1     inf        240\n",
      "            2,3           3.5          0.946        8.2    7.45        201\n",
      "          2,3,3          11.4          0.890        7.6    0.93        162\n",
      "              3           1.1          0.977        5.0     inf       4669\n",
      "            3,3           3.3          0.967       12.0    2.40       4211\n",
      "          3,3,3           8.1          0.960       19.9    1.66       3757\n",
      "        3,3,3,3          18.3          0.941       41.5    2.09       2834\n",
      "      3,3,3,3,3          35.2          0.930       50.5    1.22       1761\n",
      "    3,3,3,3,3,3          64.9          0.929       97.9    1.94       1102\n",
      "  3,3,3,3,3,3,3         100.9          0.949      143.0    1.46        530\n",
      "3,3,3,3,3,3,3,3         133.6          0.990     1821.9   12.74        131\n",
      "              4           2.0          0.976       10.7     inf       2789\n",
      "            4,3           3.7          0.976       20.4    1.91       2293\n",
      "          4,3,3           8.3          0.967       32.5    1.59       2051\n",
      "        4,3,3,3          19.8          0.958       54.5    1.68       1700\n",
      "      4,3,3,3,3          41.0          0.958       99.5    1.83       1148\n",
      "    4,3,3,3,3,3          68.1          0.956      116.1    1.17        521\n",
      "  4,3,3,3,3,3,3          78.5          0.979      110.7    0.95        248\n",
      "4,3,3,3,3,3,3,3         114.1          0.984      177.8    1.61        166\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Step 1\"\"\"\n",
    "# Extract the collection file or deck file to get the .anki21 database.\n",
    "with zipfile.ZipFile(f'{filename}', 'r') as zip_ref:\n",
    "    zip_ref.extractall('./')\n",
    "    print(\"Deck file extracted successfully!\")\n",
    "\n",
    "\"\"\"Step 2\"\"\"\n",
    "if os.path.isfile(\"collection.anki21b\"):\n",
    "    os.remove(\"collection.anki21b\")\n",
    "    raise Exception(\n",
    "        \"Please export the file with `support older Anki versions` if you use the latest version of Anki.\")\n",
    "elif os.path.isfile(\"collection.anki21\"):\n",
    "    con = sqlite3.connect(\"collection.anki21\")\n",
    "elif os.path.isfile(\"collection.anki2\"):\n",
    "    con = sqlite3.connect(\"collection.anki2\")\n",
    "else:\n",
    "    raise Exception(\"Collection not exist!\")\n",
    "cur = con.cursor()\n",
    "res = cur.execute(f\"\"\"\n",
    "SELECT *\n",
    "FROM revlog\n",
    "WHERE cid IN (\n",
    "    SELECT id\n",
    "    FROM cards\n",
    "    {\"WHERE queue != -1\" if filter_out_suspended_cards else \"\"}\n",
    ")\n",
    "\"\"\"\n",
    ")\n",
    "revlog = res.fetchall()\n",
    "if len(revlog) == 0:\n",
    "    raise Exception(\"No review log found!\")\n",
    "df = pd.DataFrame(revlog)\n",
    "df.columns = ['id', 'cid', 'usn', 'r', 'ivl', 'last_lvl', 'factor', 'time', 'type']\n",
    "df = df[(df['cid'] <= time.time() * 1000) &\n",
    "        (df['id'] <= time.time() * 1000)].copy()\n",
    "\n",
    "df_set_due_date = df[(df['type'] == 4) & (df['ivl'] > 0)]\n",
    "df.drop(df_set_due_date.index, inplace=True)\n",
    "\n",
    "df['create_date'] = pd.to_datetime(df['cid'] // 1000, unit='s')\n",
    "df['create_date'] = df['create_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df['review_date'] = pd.to_datetime(df['id'] // 1000, unit='s')\n",
    "df['review_date'] = df['review_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df.drop(df[df['review_date'].dt.year < 2006].index, inplace=True)\n",
    "df.sort_values(by=['cid', 'id'], inplace=True, ignore_index=True)\n",
    "\n",
    "df['is_learn_start'] = (df['type'] == 0) & (df['type'].shift() != 0)\n",
    "df['sequence_group'] = df['is_learn_start'].cumsum()\n",
    "last_learn_start = df[df['is_learn_start']].groupby('cid')['sequence_group'].last()\n",
    "df['last_learn_start'] = df['cid'].map(last_learn_start).fillna(0).astype(int)\n",
    "df['mask'] = df['last_learn_start'] <= df['sequence_group']\n",
    "df = df[df['mask'] == True].copy()\n",
    "df.drop(columns=['is_learn_start', 'sequence_group', 'last_learn_start', 'mask'], inplace=True)\n",
    "df = df[(df['type'] != 4)].copy()\n",
    "\n",
    "type_sequence = np.array(df['type'])\n",
    "time_sequence = np.array(df['time'])\n",
    "df.to_csv(\"revlog.csv\", index=False)\n",
    "print(\"revlog.csv saved.\")\n",
    "\n",
    "df = df[(df['type'] != 3) | (df['factor'] != 0)].copy()\n",
    "df['real_days'] = df['review_date'] - timedelta(hours=int(next_day_starts_at))\n",
    "df['real_days'] = pd.DatetimeIndex(df['real_days'].dt.floor('D', ambiguous='infer', nonexistent='shift_forward')).to_julian_date()\n",
    "df.drop_duplicates(['cid', 'real_days'], keep='first', inplace=True)\n",
    "df['delta_t'] = df.real_days.diff()\n",
    "df.dropna(inplace=True)\n",
    "df['i'] = df.groupby('cid').cumcount() + 1\n",
    "df.loc[df['i'] == 1, 'delta_t'] = 0\n",
    "df = df.groupby('cid').filter(lambda group: group['type'].iloc[0] == 0)\n",
    "df['prev_type'] = df.groupby('cid')['type'].shift(1).fillna(0).astype(int)\n",
    "df['helper'] = ((df['type'] == 0) & ((df['prev_type'] == 1) | (df['prev_type'] == 2)) & (df['i'] > 1)).astype(int)\n",
    "df['helper'] = df.groupby('cid')['helper'].cumsum()\n",
    "df = df[df['helper'] == 0]\n",
    "del df['prev_type']\n",
    "del df['helper']\n",
    "\n",
    "def cum_concat(x):\n",
    "    return list(accumulate(x))\n",
    "\n",
    "t_history = df.groupby('cid', group_keys=False)['delta_t'].apply(lambda x: cum_concat([[int(i)] for i in x]))\n",
    "df['t_history']=[','.join(map(str, item[:-1])) for sublist in t_history for item in sublist]\n",
    "r_history = df.groupby('cid', group_keys=False)['r'].apply(lambda x: cum_concat([[i] for i in x]))\n",
    "df['r_history']=[','.join(map(str, item[:-1])) for sublist in r_history for item in sublist]\n",
    "df = df.groupby('cid').filter(lambda group: group['id'].min() > time.mktime(datetime.strptime(revlog_start_date, \"%Y-%m-%d\").timetuple()) * 1000)\n",
    "df['y'] = df['r'].map(lambda x: {1: 0, 2: 1, 3: 1, 4: 1}[x])\n",
    "df.to_csv('revlog_history.tsv', sep=\"\\t\", index=False)\n",
    "print(\"Trainset saved.\")\n",
    "\n",
    "df['retention'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['y'].transform('mean')\n",
    "df['total_cnt'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['id'].transform('count')\n",
    "print(\"Retention calculated.\")\n",
    "\n",
    "df = df.drop(columns=['id', 'cid', 'usn', 'ivl', 'last_lvl', 'factor', 'time', 'type', 'create_date', 'review_date', 'real_days', 'r', 't_history', 'y'])\n",
    "df.drop_duplicates(inplace=True)\n",
    "df['retention'] = df['retention'].map(lambda x: max(min(0.99, x), 0.01))\n",
    "\n",
    "def cal_stability(group: pd.DataFrame) -> pd.DataFrame:\n",
    "    group_cnt = sum(group['total_cnt'])\n",
    "    if group_cnt < 10:\n",
    "        return pd.DataFrame()\n",
    "    group['group_cnt'] = group_cnt\n",
    "    if group['i'].values[0] > 1:\n",
    "        r_ivl_cnt = sum(group['delta_t'] * group['retention'].map(np.log) * pow(group['total_cnt'], 2))\n",
    "        ivl_ivl_cnt = sum(group['delta_t'].map(lambda x: x ** 2) * pow(group['total_cnt'], 2))\n",
    "        group['stability'] = round(np.log(0.9) / (r_ivl_cnt / ivl_ivl_cnt), 1)\n",
    "    else:\n",
    "        group['stability'] = 0.0\n",
    "    group['avg_retention'] = round(sum(group['retention'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 3)\n",
    "    group['avg_interval'] = round(sum(group['delta_t'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 1)\n",
    "    del group['total_cnt']\n",
    "    del group['retention']\n",
    "    del group['delta_t']\n",
    "    return group\n",
    "\n",
    "df = df.groupby(by=['r_history'], group_keys=False).progress_apply(cal_stability)\n",
    "print(\"Stability calculated.\")\n",
    "df.reset_index(drop = True, inplace = True)\n",
    "df.drop_duplicates(inplace=True)\n",
    "df.sort_values(by=['r_history'], inplace=True, ignore_index=True)\n",
    "\n",
    "if df.shape[0] > 0:\n",
    "    for idx in tqdm(df.index, desc=\"analysis\"):\n",
    "        item = df.loc[idx]\n",
    "        index = df[(df['i'] == item['i'] + 1) & (df['r_history'].str.startswith(item['r_history']))].index\n",
    "        df.loc[index, 'last_stability'] = item['stability']\n",
    "    df['factor'] = round(df['stability'] / df['last_stability'], 2)\n",
    "    df = df[(df['i'] >= 2) & (df['group_cnt'] >= 100)].copy()\n",
    "    df['last_recall'] = df['r_history'].map(lambda x: x[-1])\n",
    "    df = df[df.groupby(['i', 'r_history'], group_keys=False)['group_cnt'].transform(max) == df['group_cnt']]\n",
    "    df.to_csv('./stability_for_analysis.tsv', sep='\\t', index=None)\n",
    "    print(\"Analysis saved!\")\n",
    "    caption = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "    analysis = df[df['r_history'].str.contains(r'^[1-4][^124]*$', regex=True)][['r_history', 'avg_interval', 'avg_retention', 'stability', 'factor', 'group_cnt']].to_string(index=False)\n",
    "    print(caption + analysis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "init_w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2, -0.2, 0.2, 1]\n",
    "\n",
    "class FSRS(nn.Module):\n",
    "    def __init__(self, w: List[float]):\n",
    "        super(FSRS, self).__init__()\n",
    "        self.w = nn.Parameter(torch.tensor(w, dtype=torch.float32))\n",
    "\n",
    "    def stability_after_success(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = state[:,0] * (1 + torch.exp(self.w[6]) *\n",
    "                        (11 - new_d) *\n",
    "                        torch.pow(state[:,0], self.w[7]) *\n",
    "                        (torch.exp((1 - r) * self.w[8]) - 1))\n",
    "        return new_s\n",
    "\n",
    "    def stability_after_failure(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = self.w[9] * torch.pow(new_d, self.w[10]) * (torch.pow(\n",
    "            state[:,0] + 1, self.w[11]) - 1) * torch.exp((1 - r) * self.w[12])\n",
    "        return new_s\n",
    "\n",
    "    def step(self, X: Tensor, state: Tensor) -> Tensor:\n",
    "        '''\n",
    "        :param X: shape[batch_size, 2], X[:,0] is elapsed time, X[:,1] is rating\n",
    "        :param state: shape[batch_size, 2], state[:,0] is stability, state[:,1] is difficulty\n",
    "        :return state:\n",
    "        '''\n",
    "        if torch.equal(state, torch.zeros_like(state)):\n",
    "            # first learn, init memory states\n",
    "            new_s = self.w[0] + self.w[1] * (X[:,1] - 1)\n",
    "            new_d = self.w[2] + self.w[3] * (X[:,1] - 3)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "        else:\n",
    "            r = torch.exp(np.log(0.9) * X[:,0] / state[:,0])\n",
    "            new_d = state[:,1] + self.w[4] * (X[:,1] - 3)\n",
    "            new_d = self.mean_reversion(self.w[2], new_d)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "            condition = X[:,1] > 1\n",
    "            new_s = torch.where(condition, self.stability_after_success(state, new_d, r), self.stability_after_failure(state, new_d, r))\n",
    "        new_s = new_s.clamp(0.1, 36500)\n",
    "        return torch.stack([new_s, new_d], dim=1)\n",
    "\n",
    "    def forward(self, inputs: Tensor, state: Optional[Tensor]=None) -> Tensor:\n",
    "        '''\n",
    "        :param inputs: shape[seq_len, batch_size, 2]\n",
    "        '''\n",
    "        if state is None:\n",
    "            state = torch.zeros((inputs.shape[1], 2))\n",
    "        outputs = []\n",
    "        for X in inputs:\n",
    "            state = self.step(X, state)\n",
    "            outputs.append(state)\n",
    "        return torch.stack(outputs), state\n",
    "\n",
    "    def mean_reversion(self, init: Tensor, current: Tensor) -> Tensor:\n",
    "        return self.w[5] * init + (1-self.w[5]) * current\n",
    "\n",
    "class WeightClipper:\n",
    "    def __init__(self, frequency: int=1):\n",
    "        self.frequency = frequency\n",
    "\n",
    "    def __call__(self, module):\n",
    "        if hasattr(module, 'w'):\n",
    "            w = module.w.data\n",
    "            w[0] = w[0].clamp(0.1, 10)\n",
    "            w[1] = w[1].clamp(0.1, 5)\n",
    "            w[2] = w[2].clamp(1, 10)\n",
    "            w[3] = w[3].clamp(-5, -0.1)\n",
    "            w[4] = w[4].clamp(-5, -0.1)\n",
    "            w[5] = w[5].clamp(0.05, 0.5)\n",
    "            w[6] = w[6].clamp(0, 2)\n",
    "            w[7] = w[7].clamp(-0.8, -0.15)\n",
    "            w[8] = w[8].clamp(0.01, 1.5)\n",
    "            w[9] = w[9].clamp(0.5, 5)\n",
    "            w[10] = w[10].clamp(-2, -0.01)\n",
    "            w[11] = w[11].clamp(0.01, 0.9)\n",
    "            w[12] = w[12].clamp(0.01, 2)\n",
    "            module.w.data = w\n",
    "\n",
    "def lineToTensor(line: str) -> Tensor:\n",
    "    ivl = line[0].split(',')\n",
    "    response = line[1].split(',')\n",
    "    tensor = torch.zeros(len(response), 2)\n",
    "    for li, response in enumerate(response):\n",
    "        tensor[li][0] = int(ivl[li])\n",
    "        tensor[li][1] = int(response)\n",
    "    return tensor\n",
    "\n",
    "class RevlogDataset(Dataset):\n",
    "    def __init__(self, dataframe: pd.DataFrame):\n",
    "        if dataframe.empty:\n",
    "            raise ValueError('Training data is inadequate.')\n",
    "        padded = pad_sequence(dataframe['tensor'].to_list(), batch_first=True, padding_value=0)\n",
    "        self.x_train = padded.int()\n",
    "        self.t_train = torch.tensor(dataframe['delta_t'].values, dtype=torch.int)\n",
    "        self.y_train = torch.tensor(dataframe['y'].values, dtype=torch.float)\n",
    "        self.seq_len = torch.tensor(dataframe['tensor'].map(len).values, dtype=torch.long)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.x_train[idx], self.t_train[idx], self.y_train[idx], self.seq_len[idx]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.y_train)\n",
    "\n",
    "class RevlogSampler(Sampler[List[int]]):\n",
    "    def __init__(self, data_source: RevlogDataset, batch_size: int):\n",
    "        self.data_source = data_source\n",
    "        self.batch_size = batch_size\n",
    "        lengths = np.array(data_source.seq_len)\n",
    "        indices = np.argsort(lengths)\n",
    "        full_batches, remainder = divmod(indices.size, self.batch_size)\n",
    "        if full_batches > 0:\n",
    "            if remainder == 0:\n",
    "                self.batch_indices = np.split(indices, full_batches)\n",
    "            else:\n",
    "                self.batch_indices = np.split(indices[:-remainder], full_batches)\n",
    "        else:\n",
    "            self.batch_indices = []\n",
    "        if remainder > 0:\n",
    "            self.batch_indices.append(indices[-remainder:])\n",
    "        self.batch_nums = len(self.batch_indices)\n",
    "        # seed = int(torch.empty((), dtype=torch.int64).random_().item())\n",
    "        seed = 2023\n",
    "        self.generator = torch.Generator()\n",
    "        self.generator.manual_seed(seed)\n",
    "\n",
    "    def __iter__(self):\n",
    "        yield from (self.batch_indices[idx] for idx in torch.randperm(self.batch_nums, generator=self.generator).tolist())\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data_source)\n",
    "\n",
    "\n",
    "def collate_fn(batch):\n",
    "    sequences, delta_ts, labels, seq_lens = zip(*batch)\n",
    "    sequences_packed = pack_padded_sequence(torch.stack(sequences, dim=1), lengths=torch.stack(seq_lens), batch_first=False, enforce_sorted=False)\n",
    "    sequences_padded, length = pad_packed_sequence(sequences_packed, batch_first=False)\n",
    "    sequences_padded = torch.as_tensor(sequences_padded)\n",
    "    seq_lens = torch.as_tensor(length)\n",
    "    delta_ts = torch.as_tensor(delta_ts)\n",
    "    labels = torch.as_tensor(labels)\n",
    "    return sequences_padded, delta_ts, labels, seq_lens\n",
    "\n",
    "class Trainer:\n",
    "    def __init__(self, train_set: pd.DataFrame, test_set: pd.DataFrame, init_w: List[float], n_epoch: int=1, lr: float=1e-2, batch_size: int=256) -> None:\n",
    "        self.model = FSRS(init_w)\n",
    "        self.optimizer = torch.optim.Adam(self.model.parameters(), lr=lr)\n",
    "        self.clipper = WeightClipper()\n",
    "        self.batch_size = batch_size\n",
    "        self.build_dataset(train_set, test_set)\n",
    "        self.n_epoch = n_epoch\n",
    "        self.batch_nums = self.next_train_data_loader.batch_sampler.batch_nums\n",
    "        self.scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(self.optimizer, T_max=self.batch_nums * n_epoch)\n",
    "        self.avg_train_losses = []\n",
    "        self.avg_eval_losses = []\n",
    "        self.loss_fn = nn.BCELoss(reduction='sum')\n",
    "\n",
    "    def build_dataset(self, train_set: pd.DataFrame, test_set: pd.DataFrame):\n",
    "        pre_train_set = train_set[train_set['i'] == 2]\n",
    "        self.pre_train_set = RevlogDataset(pre_train_set)\n",
    "        sampler = RevlogSampler(self.pre_train_set, batch_size=self.batch_size)\n",
    "        self.pre_train_data_loader = DataLoader(self.pre_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        next_train_set = train_set[train_set['i'] > 2]\n",
    "        self.next_train_set = RevlogDataset(next_train_set)\n",
    "        sampler = RevlogSampler(self.next_train_set, batch_size=self.batch_size)\n",
    "        self.next_train_data_loader = DataLoader(self.next_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.train_set = RevlogDataset(train_set)\n",
    "        sampler = RevlogSampler(self.train_set, batch_size=self.batch_size)\n",
    "        self.train_data_loader = DataLoader(self.train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.test_set = RevlogDataset(test_set)\n",
    "        sampler = RevlogSampler(self.test_set, batch_size=self.batch_size)\n",
    "        self.test_data_loader = DataLoader(self.test_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "        print(\"dataset built\")\n",
    "\n",
    "    def train(self, verbose: bool=True):\n",
    "        # pretrain\n",
    "        best_loss = np.inf\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        pbar = tqdm(desc=\"pre-train\", colour=\"red\", total=len(self.pre_train_data_loader) * self.n_epoch)\n",
    "        for k in range(self.n_epoch):\n",
    "            for i, batch in enumerate(self.pre_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                self.optimizer.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(n=real_batch_size)\n",
    "\n",
    "        pbar.close()\n",
    "        for name, param in self.model.named_parameters():\n",
    "            tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "\n",
    "        epoch_len = len(self.next_train_data_loader)\n",
    "        pbar = tqdm(desc=\"train\", colour=\"red\", total=epoch_len*self.n_epoch)\n",
    "        print_len = max(self.batch_nums*self.n_epoch // 10, 1)\n",
    "        for k in range(self.n_epoch):\n",
    "            weighted_loss, w = self.eval()\n",
    "            if weighted_loss < best_loss:\n",
    "                best_loss = weighted_loss\n",
    "                best_w = w\n",
    "\n",
    "            for i, batch in enumerate(self.next_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                for param in self.model.parameters():\n",
    "                    param.grad[:2] = torch.zeros(2)\n",
    "                self.optimizer.step()\n",
    "                self.scheduler.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(real_batch_size)\n",
    "\n",
    "                if verbose and (k * self.batch_nums + i + 1) % print_len == 0:\n",
    "                    tqdm.write(f\"iteration: {k * epoch_len + (i + 1) * self.batch_size}\")\n",
    "                    for name, param in self.model.named_parameters():\n",
    "                        tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "        pbar.close()\n",
    "\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        return best_w\n",
    "\n",
    "    def eval(self):\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            sequences, delta_ts, labels, seq_lens = self.train_set.x_train, self.train_set.t_train, self.train_set.y_train, self.train_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            tran_loss = self.loss_fn(retentions, labels)/len(self.train_set)\n",
    "            self.avg_train_losses.append(tran_loss)\n",
    "            tqdm.write(f\"Loss in trainset: {tran_loss:.4f}\")\n",
    "\n",
    "            sequences, delta_ts, labels, seq_lens = self.test_set.x_train, self.test_set.t_train, self.test_set.y_train, self.test_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            test_loss = self.loss_fn(retentions, labels)/len(self.test_set)\n",
    "            self.avg_eval_losses.append(test_loss)\n",
    "            tqdm.write(f\"Loss in testset: {test_loss:.4f}\")\n",
    "\n",
    "            w = list(map(lambda x: round(float(x), 4), dict(self.model.named_parameters())['w'].data))\n",
    "\n",
    "            weighted_loss = (tran_loss * len(self.train_set) + test_loss * len(self.test_set)) / (len(self.train_set) + len(self.test_set))\n",
    "\n",
    "            return weighted_loss, w\n",
    "\n",
    "    def plot(self):\n",
    "        fig = plt.figure()\n",
    "        ax = fig.gca()\n",
    "        ax.plot(self.avg_train_losses, label='train')\n",
    "        ax.plot(self.avg_eval_losses, label='test')\n",
    "        ax.set_xlabel('epoch')\n",
    "        ax.set_ylabel('loss')\n",
    "        ax.legend()\n",
    "        return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ae0b9a8b94f04805aeba6e7fa532ce63",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/88151 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorized!\n",
      "TRAIN: 57372 TEST: 30779\n",
      "dataset built\n",
      "Loss in trainset: 0.3445\n",
      "Loss in testset: 0.3234\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8177cca6f0e54e9d9e9b846abc2e9964",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/15276 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2588, 1.8518, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a8be4cedfd644cf3921b195484c47235",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156840 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3416\n",
      "Loss in testset: 0.3207\n",
      "iteration: 15360\n",
      "w: [1.2327, 2.0554, 5.179, -1.2946, -1.2461, 0.05, 1.5258, -0.15, 0.9321, 2.2179, -0.1284, 0.4269, 1.145]\n",
      "iteration: 30720\n",
      "w: [1.2313, 2.0664, 5.2488, -1.8182, -1.5073, 0.05, 1.5841, -0.15, 0.9915, 2.2505, -0.1016, 0.3683, 1.1362]\n",
      "iteration: 46080\n",
      "w: [1.2312, 2.067, 5.15, -1.8551, -1.6431, 0.05, 1.5579, -0.212, 0.9778, 2.3191, -0.0314, 0.3734, 1.0952]\n",
      "Loss in trainset: 0.3180\n",
      "Loss in testset: 0.2980\n",
      "iteration: 60984\n",
      "w: [1.2312, 2.067, 5.143, -1.9465, -1.7376, 0.05, 1.499, -0.2727, 0.9169, 2.3271, -0.0232, 0.3224, 1.1059]\n",
      "iteration: 76344\n",
      "w: [1.2312, 2.067, 4.9392, -1.8717, -1.7053, 0.05, 1.5614, -0.2135, 0.9706, 2.3513, -0.0278, 0.2824, 1.0771]\n",
      "iteration: 91704\n",
      "w: [1.2312, 2.067, 5.034, -2.0321, -1.8294, 0.05, 1.5269, -0.2673, 0.9351, 2.418, -0.0138, 0.3236, 1.0258]\n",
      "Loss in trainset: 0.3174\n",
      "Loss in testset: 0.2974\n",
      "iteration: 106608\n",
      "w: [1.2312, 2.067, 4.9636, -2.0059, -1.837, 0.05, 1.5501, -0.2335, 0.9502, 2.4033, -0.0304, 0.2998, 0.9339]\n",
      "iteration: 121968\n",
      "w: [1.2312, 2.067, 4.9474, -1.9934, -1.8559, 0.05, 1.5419, -0.2346, 0.9385, 2.4348, -0.0101, 0.324, 0.9236]\n",
      "iteration: 137328\n",
      "w: [1.2312, 2.067, 4.9336, -1.9962, -1.8551, 0.05, 1.5414, -0.2252, 0.9356, 2.4389, -0.01, 0.3248, 0.9194]\n",
      "iteration: 152688\n",
      "w: [1.2312, 2.067, 4.9331, -1.9946, -1.8563, 0.05, 1.5355, -0.2319, 0.9294, 2.437, -0.0121, 0.321, 0.9169]\n",
      "Loss in trainset: 0.3172\n",
      "Loss in testset: 0.2972\n",
      "TRAIN: 59696 TEST: 28455\n",
      "dataset built\n",
      "Loss in trainset: 0.3312\n",
      "Loss in testset: 0.3495\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2163e6ac72474e0da738fd0a3ef9ed70",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/22374 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [2.0143, 2.047, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "757373b19bad497db0edd241769099d6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156714 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3271\n",
      "Loss in testset: 0.3475\n",
      "iteration: 15360\n",
      "w: [2.1098, 2.1547, 5.107, -1.2281, -1.2671, 0.0637, 1.5963, -0.15, 1.0214, 2.2308, -0.1762, 0.4517, 1.2486]\n",
      "iteration: 30720\n",
      "w: [2.1147, 2.1603, 5.2324, -1.7794, -1.5451, 0.0616, 1.5502, -0.2342, 1.0276, 2.233, -0.183, 0.4145, 1.2437]\n",
      "iteration: 46080\n",
      "w: [2.1149, 2.1605, 5.1239, -1.9714, -1.5424, 0.05, 1.5094, -0.229, 0.9976, 2.2648, -0.1505, 0.3882, 1.1345]\n",
      "Loss in trainset: 0.3052\n",
      "Loss in testset: 0.3265\n",
      "iteration: 60942\n",
      "w: [2.1149, 2.1605, 5.1508, -1.9394, -1.7237, 0.06, 1.4025, -0.2857, 0.8944, 2.2947, -0.1216, 0.3599, 1.1507]\n",
      "iteration: 76302\n",
      "w: [2.1149, 2.1605, 5.0698, -1.9652, -1.7523, 0.05, 1.4152, -0.2517, 0.913, 2.3282, -0.0867, 0.3664, 1.1025]\n",
      "iteration: 91662\n",
      "w: [2.1149, 2.1605, 4.9142, -1.8831, -1.726, 0.05, 1.4694, -0.1775, 0.9616, 2.3391, -0.075, 0.3538, 1.0513]\n",
      "Loss in trainset: 0.3034\n",
      "Loss in testset: 0.3245\n",
      "iteration: 106524\n",
      "w: [2.1149, 2.1605, 4.9144, -1.9197, -1.7383, 0.05, 1.4244, -0.2145, 0.9111, 2.3571, -0.0553, 0.3573, 1.0281]\n",
      "iteration: 121884\n",
      "w: [2.1149, 2.1605, 4.8932, -1.9304, -1.7488, 0.05, 1.4292, -0.2032, 0.9132, 2.3709, -0.0399, 0.358, 1.0078]\n",
      "iteration: 137244\n",
      "w: [2.1149, 2.1605, 4.8981, -1.9489, -1.7595, 0.05, 1.4216, -0.2034, 0.9036, 2.3729, -0.0376, 0.3557, 1.0015]\n",
      "iteration: 152604\n",
      "w: [2.1149, 2.1605, 4.8954, -1.9454, -1.7602, 0.05, 1.4195, -0.2058, 0.9011, 2.3701, -0.0404, 0.3518, 0.9971]\n",
      "Loss in trainset: 0.3034\n",
      "Loss in testset: 0.3244\n",
      "TRAIN: 59234 TEST: 28917\n",
      "dataset built\n",
      "Loss in trainset: 0.3359\n",
      "Loss in testset: 0.3395\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "def88954bf1d4962bb12579e6085a2bf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/20916 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2804, 1.8287, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "01fa6803c81449668b12ae4832e3874d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156786 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3334\n",
      "Loss in testset: 0.3361\n",
      "iteration: 15360\n",
      "w: [1.2103, 1.9125, 5.0991, -1.3182, -1.2731, 0.05, 1.541, -0.1734, 0.9744, 2.1936, -0.118, 0.4241, 1.1041]\n",
      "iteration: 30720\n",
      "w: [1.2066, 1.9168, 5.1774, -1.6641, -1.5697, 0.05, 1.4703, -0.2088, 0.9292, 2.1774, -0.1366, 0.3703, 0.9256]\n",
      "iteration: 46080\n",
      "w: [1.2065, 1.917, 5.0674, -1.8506, -1.6174, 0.05, 1.4995, -0.2079, 0.9437, 2.2436, -0.07, 0.3382, 0.8381]\n",
      "Loss in trainset: 0.3103\n",
      "Loss in testset: 0.3116\n",
      "iteration: 60966\n",
      "w: [1.2065, 1.917, 4.972, -1.7378, -1.7459, 0.05, 1.4746, -0.23, 0.909, 2.3176, -0.015, 0.336, 0.8996]\n",
      "iteration: 76326\n",
      "w: [1.2065, 1.917, 4.8698, -1.7574, -1.7484, 0.05, 1.4465, -0.2468, 0.8738, 2.3681, -0.01, 0.3405, 0.9234]\n",
      "iteration: 91686\n",
      "w: [1.2065, 1.917, 4.828, -1.8494, -1.8207, 0.05, 1.5013, -0.1816, 0.9203, 2.3817, -0.01, 0.3185, 0.8715]\n",
      "Loss in trainset: 0.3099\n",
      "Loss in testset: 0.3112\n",
      "iteration: 106572\n",
      "w: [1.2065, 1.917, 4.8078, -1.9001, -1.8236, 0.0544, 1.5052, -0.1982, 0.9196, 2.3961, -0.0121, 0.318, 0.8283]\n",
      "iteration: 121932\n",
      "w: [1.2065, 1.917, 4.7951, -1.9133, -1.8411, 0.05, 1.4928, -0.2167, 0.9042, 2.4189, -0.01, 0.3299, 0.8288]\n",
      "iteration: 137292\n",
      "w: [1.2065, 1.917, 4.8086, -1.942, -1.8601, 0.05, 1.4832, -0.2225, 0.8932, 2.4228, -0.0106, 0.3289, 0.8209]\n",
      "iteration: 152652\n",
      "w: [1.2065, 1.917, 4.8071, -1.9421, -1.8617, 0.05, 1.4814, -0.2238, 0.891, 2.4222, -0.0116, 0.3275, 0.8191]\n",
      "Loss in trainset: 0.3098\n",
      "Loss in testset: 0.3112\n",
      "\n",
      "Training finished!\n"
     ]
    },
    {
     "data": {
      "image/png": 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RI0cycuRIZs2adVLb6dOn89tvv9G8uUm3GYpPGDu0My0ig9hx4AjP/7DO7HJERKQKTA9Ar776Kn//+98ZOXIkXbp04Z133iE4OJh///vfFbYfOHAgV199NZ07d6Zdu3Y88MAD9OjRg19++aVcu127dnHffffxn//8B39/PcNJ6k5ogB8vDnNNhU39bRuLNu4zuSIRETkdUwNQUVERy5YtIzk52b3ParWSnJxMWlraaY83DIN58+aRkZHB+eef797vdDq5+eabeeSRR+jatetpz1NYWEhubm65l0h1nJMQzc1nuxb8evSLVeQdNeeiPhERqRpTA9C+fftwOBzExMSU2x8TE0NmZmalx+Xk5BAaGordbmfo0KFMnDiRQYMGub/+wgsv4Ofnx/3331+lOlJTU4mIiHC/4uLiatYh8WmjL+tEXFQQuw4d4bkZmgoTEfFkpk+B1URYWBgrV65k6dKlPPvss6SkpDB//nwAli1bxhtvvMGUKVPcD1o7nTFjxpCTk+N+7dixow6rl4YqJMCPl4YlAvDfJdtZsD7b5IpExBPpEZxnprb+/UwNQNHR0dhsNvbu3Vtu/969e0/5jBCr1UpCQgJJSUmMGjWKYcOGkZqaCsDChQvJysqiVatW+Pn54efnx7Zt2xg1ahTx8fEVni8gIIDw8PByL5GaOLttY24dEA/AY1+sIueIpsJExMVmcz03sKioyORKvFtBgesBsmd6fa+pj8Kw2+306tWLefPmcdVVVwGu63fmzZtX7pa503E6nRQWFgJw8803l7umCGDw4MHcfPPNjBw5stZqF6nMo5d2ZH5GFlv3F/DMd3/y0rWJZpckIh7Az8+P4OBgsrOz8ff3x2r1ykkY0xiGQUFBAVlZWURGRroDZU2Z/iywlJQUbrnlFnr37k3fvn15/fXXyc/Pd4eVESNG0KJFC/cIT2pqKr1796Zdu3YUFhYyY8YMpk6dyuTJkwFo3LgxjRs3Lvce/v7+xMbG0rFjx/rtnPikYLsfL1+byLXvpvH5sp1c1j2WizrFnP5AEWnQLBYLzZo1Y8uWLWzbts3scrxWZGRkrTxJ3vQANHz4cLKzsxk3bhyZmZkkJSUxc+ZM94XR27dvL5eS8/Pzufvuu9m5cydBQUF06tSJTz75hOHDh5vVBZGT9I6P4vZz2/D+wi2M/nI1cx6KIiJYyzGI+Dq73U779u01DVZD/v7+Zzzyc4zF0NVYJ8nNzSUiIoKcnBxdDyQ1drTYwZA3F7I5O59rzmrBq8OTzC5JRKRBq87Pb01AitSRQH8bL1+biNUC01bsYvbaypd2EBGR+qUAJFKHerZqxB3ntwPg8elrOJivYW8REU+gACRSxx5Mbk/7pqHsO1zI+G/Wml2OiIigACRS545NhdmsFr75Yzc/rN5jdkkiIj5PAUikHiTGRXLXBa6psH9+tYb9hwtNrkhExLcpAInUk/suTqBTbBj784sY97WmwkREzKQAJFJPAvxcU2F+Vgvfr97Dd6t2m12SiIjPUgASqUfdWkRwz4UJADzx1Rqy8zQVJiJiBgUgkXp2z4UJdGkWzsGCYv751Wo9GVpExAQKQCL1zO5n5eVrE/G3WZi1di/f/KGpMBGR+qYAJGKCLs3Duf+i9gCM+3otWblHTa5IRMS3KACJmOTOge3o3iKCnCPFPD5dU2EiIvVJAUjEJP4211SY3WZlbnoW05bvMrskERGfoQAkYqKOsWE8OMg1Ffbkt2vJzNFUmIhIfVAAEjHZHee1JTEukryjJYyetkpTYSIi9UABSMRkfjYrr1zbA7uflfkZ2Xz++06zSxIRafAUgEQ8QELTMB6+pAMAE777k12HjphckYhIw6YAJOIh/nZuW3q2iiSvsITRX2oqTESkLikAiXgIm9XCy9cmEuBnZeGGffy/JdvNLklEpMFSABLxIG2bhPLopZ0AePb7dHYcKDC5IhGRhkkBSMTDjBwQT9/4KAqKHDz6xSqcTk2FiYjUNgUgEQ9jtVp4cVgPgvxtpG3ezyeLt5ldkohIg6MAJOKB4qNDGH2ZayosdcY6tu3PN7kiEZGGRQFIxEPdfHZr+rdtzJFiB498rqkwEZHapAAk4qGOTYWF2G0s2XqAKb9uNbskEZEGQwFIxIPFRQXz+NDOALw4ax2bsw+bXJGISMOgACTi4f6vbyvOTYjmaLGTR75YhUNTYSIiZ0wBSMTDWSwWXhjWg9AAP5ZtO8i/f9lidkkiIl5PAUjEC7SIDOKJy11TYS/NzmBjlqbCRETOhAKQiJe4rnccF3RoQlGJk1Gf/0GJw2l2SSIiXksBSMRLWCwWnv9rd8IC/fhjxyHeX6ipMBGRmlIAEvEizSKCGH9FVwBem7Oe9XvzTK5IRMQ7KQCJeJm/9mzBxZ2aUuRwMup/f1CsqTARkWpTABLxMhaLheeu6U5EkD+rd+Xw7oJNZpckIuJ1FIBEvFBMeCBP/cU1FfbGvA2k78k1uSIREe+iACTipa5Mas4lXWIodhiaChMRqSYFIBEvZbFYePbq7jQK9ufPPblM+mmj2SWJiHgNBSARL9YkLICnr+wGwFs/bmTNrhyTKxIR8Q4KQCJe7vIezRjSPZYSp8HDn/9BUYmmwkRETkcBSMTLWSwWJlzZjcYhdtZl5jHxxw1mlyQi4vEUgEQagMahATxzlWsq7O35m/hjxyFzCxIR8XAKQCINxGXdm3FFYnMcpVNhR4sdZpckIuKxFIBEGpCn/9KV6NAANmQd5vW5mgoTEamMApBIA9IoxM5zV7umwt77eRPLtx80uSIREc+kACTSwFzSNZarz2qB00BTYSIilVAAEmmAxl/RhaZhAWzOzueV2RlmlyMi4nEUgEQaoMhgO8//tTsA//plC79vPWByRSIinkUBSKSBuqhTDNf2aolROhV2pEhTYSIixygAiTRg/7y8C80iAtm6v4AXZ60zuxwREY+hACTSgEUE+fP8X3sA8OGirfy2eb/JFYmIeAYFIJEG7oIOTbihbxwAj36xivzCEpMrEhExnwKQiA94fEhnWkQGsf1AAS/M1FSYiIgCkIgPCAv054XSqbCP07bx68Z9JlckImIuBSARH3Fu+2huOrsVAI98sYrDmgoTER+mACTiQ8Zc1pmWjYLYdegIz81IN7scERHTKACJ+JCQAD9eGpYIwP9bvJ2f12ebXJGIiDkUgER8TP92jbl1QDwAo79cRe7RYnMLEhExgQKQiA969NKOtG4czO6cozz7nabCRMT3KACJ+KBgu2sqzGKBz37fwU8ZWWaXJCJSrxSARHxU3zZR3HZOG8A1FZZToKkwEfEdHhGAJk2aRHx8PIGBgfTr148lS5ZU2nbatGn07t2byMhIQkJCSEpKYurUqeXaPPnkk3Tq1ImQkBAaNWpEcnIyixcvrutuiHidhy/pSNvoEPbmFvL0d3+aXY6ISL0xPQB99tlnpKSkMH78eJYvX05iYiKDBw8mK6viIfmoqCjGjh1LWloaq1atYuTIkYwcOZJZs2a523To0IG33nqL1atX88svvxAfH88ll1xCdrbueBEpK8hu46VrE7Fa4MvlO5n7516zSxIRqRcWwzAMMwvo168fffr04a233gLA6XQSFxfHfffdx+jRo6t0jp49ezJ06FAmTJhQ4ddzc3OJiIhg7ty5XHzxxac937H2OTk5hIeHV70zIl4qdUY67/68mSZhAcx56Hwig+1mlyQiUm3V+flt6ghQUVERy5YtIzk52b3ParWSnJxMWlraaY83DIN58+aRkZHB+eefX+l7vPfee0RERJCYmFhhm8LCQnJzc8u9RHzJQ4M60K5JCNl5hYz/Zq3Z5YiI1DlTA9C+fftwOBzExMSU2x8TE0NmZmalx+Xk5BAaGordbmfo0KFMnDiRQYMGlWvz3XffERoaSmBgIK+99hpz5swhOjq6wvOlpqYSERHhfsXFxZ1550S8SKC/jVeuS8Jqga9X7mbmmj1mlyQiUqdMvwaoJsLCwli5ciVLly7l2WefJSUlhfnz55drc+GFF7Jy5Up+/fVXLr30Uq677rpKrysaM2YMOTk57teOHTvqoRciniUpLpI7L2gHwNjpa9h/uNDkikRE6o6pASg6OhqbzcbeveUvvNy7dy+xsbGVHme1WklISCApKYlRo0YxbNgwUlNTy7UJCQkhISGBs88+mw8++AA/Pz8++OCDCs8XEBBAeHh4uZeIL3oguT0dYkLZn1/EOE2FiUgDZmoAstvt9OrVi3nz5rn3OZ1O5s2bR//+/at8HqfTSWHhqX9brUobEV8X4GfjlWuTsFktfL9qD9+t2m12SSIidcL0KbCUlBTef/99PvroI9LT07nrrrvIz89n5MiRAIwYMYIxY8a426empjJnzhw2b95Meno6r7zyClOnTuWmm24CID8/n8cff5zffvuNbdu2sWzZMm677TZ27drFtddea0ofRbxJ95YR3DPQNRX2xFdryM7TLw4i0vD4mV3A8OHDyc7OZty4cWRmZpKUlMTMmTPdF0Zv374dq/V4TsvPz+fuu+9m586dBAUF0alTJz755BOGDx8OgM1mY926dXz00Ufs27ePxo0b06dPHxYuXEjXrl1N6aOIt7n3ovbM/nMv6zLz+OdXq3nnpl5YLBazyxIRqTWmrwPkibQOkAis3Z3DlW8tosRp8Mb1SVyZ1MLskkRETslr1gESEc/VtXkE913UHoBxX68lK/eoyRWJiNQeBSARqdTdF7ajW4twco4U8/j01WjAWEQaCgUgEamUv83KK9cm4W+zMDc9i+krdpldkohIrVAAEpFT6hgbxoPJHQB48pu1ZOZoKkxEvJ8CkIic1j/Ob0tiywhyj5YwZtoqTYWJiNdTABKR0/KzWXn52kTsflZ+ysjm82U7zS5JROSMKACJSJW0jwlj1CDXVNiEb/9k96EjJlckIlJzCkAiUmW3n9eWs1pFkldYwmNfaipMRLyXApCIVJnNauHlaxMJ8LOycMM+Pl26w+ySRERqRAFIRKqlXZNQHhncEYBnvvuTnQcLTK5IRKT6FIBEpNpGntOGPvGNyC9y8OgXq3A6NRUmIt5FAUhEqs1mtfDSsEQC/a38umk//1my3eySRESqRQFIRGokPjqE0Zd2AiB1Rjrb92sqTES8hwKQiNTYiP7x9GsTRUGRg0e++ENTYSLiNRSARKTGrKVTYcF2G4u3HODjtK1mlyQiUiUKQCJyRlo1DmbMkM4APD9zHVv25ZtckYjI6SkAicgZu7FvK85JaMzRYiePfP4HDk2FiYiHUwASkTNmtVp44a89CLHb+H3bQT5ctMXskkRETkkBSERqRctGwfzz8i4AvDQrg41Zh02uSESkcgpAIlJrru8Tx3ntoykscfKwpsJExIMpAIlIrbFYXFNhYQF+rNxxiPcXbja7JBGRCikAiUitah4ZxBNXuKbCXp29ng1780yuSETkZApAIlLrru3Vkgs7NqHI4WTU539Q4nCaXZKISDkKQCJS6ywWC6nX9CA80I9VO3N492dNhYmIZ1EAEpE6ERsRyJN/6QrA63PXsy4z1+SKRESOUwASkTpz9VktGNQlhmKHwaj//UGxpsJExEMoAIlInbFYLDx7dTcig/1ZuzuXt3/aZHZJIiKAApCI1LGmYYE8fWU3ACb+uIG1u3NMrkhERAFIROrBFT2acVm3WEqcrqmwohJNhYmIuRSARKTOWSwWJlzVjagQO+sy83jrxw1mlyQiPk4BSETqRXRoABNKp8Imzd/E6p2aChMR8ygAiUi9GdqjGZf3aIbDaTDq85UUljjMLklEfJQCkIjUq6ev7EZ0qJ31ew/zxlxNhYmIORSARKReRYXYeeaq7gC8s2ATK3ccMrcgEfFJCkAiUu8u7RbLVUnNcRow6n8rOVqsqTARqV8KQCJiiif/0pUmYQFsys7ntTnrzS5HRHyMApCImCIy2E7q1a6psPcWbmbZtgMmVyQivkQBSERMk9wlhr/2bIlhwMOfr+JIkabCRKR+KADVp8zVkPY2bPoJ8jLBMMyuSMR0467oQkx4AFv25fPSrAyzyxERH+FndgE+ZeNcmPvk8b8HNYKmXaBp59JXF2jSCYKjTCtRpL5FBPnz/F97MPLDpXz46xYGd42hX9vGZpclIg2cxTA0DHGi3NxcIiIiyMnJITw8vPZOnP4trPofZKXDgU1gVPI8pLBmxwNR087QpDM06QgBobVXi4iHeeyLVXz2+w5aRQUz88HzCLbr9zMRqZ7q/PxWAKpAnQWgsoqPwr71rjCU9Wfpn+mQs73yYyJblxkxKv0zuj34BdRNjSL1KPdoMZe+9jO7c45yS//WPFX62AwRkapSADpD9RKAKlOYB9kZZUJR6Z+H91bc3mKDxgllQlEn15+N2oBNv0GLd1m4IZubP1gCwP/7ez8GtIs2uSIR8SYKQGfI1ABUmfz9kJ1+wojRn3C0kgdK2gKgSYeTR4wi4sBiqd/aRarh8emr+X+Lt9OyURAzHzyf0AAFeRGpGgWgM+SRAagihgF5e0oD0brjoSh7HRQXVHyMPax0lKjMRddNu0BoUwUj8QiHC0sY/NrP7Dp0hBv7teLZ0rWCRERORwHoDHlNAKqM0wmHtp18fdG+9eAsrviYoKiT70hr2sl1p5pIPft14z7+71+LAZj6t76c176JyRWJiDdQADpDXh+AKuMohv2bjo8SHQtHBzaf4o605mVCUemrSSewh9Rv7eJzxn29ho/TttE8IpBZD51PWKC/2SWJiIdTADpDDTYAVab4SCV3pO2o5AALNKrgjrTG7cHPXq+lS8OVX1jCZW8sZPuBAq7vE8fzf+1hdkki4uEUgM6QzwWgyhzNKXNHWpkRo/ysittb/Y7fkdakzFRaVBuw2uq3dmkQFm/ez/D3fgNgysg+DOzY1OSKRMST1XkA+uijj4iOjmbo0KEAPProo7z33nt06dKF//73v7Ru3bpmlXsIBaDTyN93fJSo7IhRYSV3pPkFQnRFd6S11IXXclpPfbuWDxdtJTbcNRUWEaSpMBGpWJ0HoI4dOzJ58mQuuugi0tLSSE5O5rXXXuO7777Dz8+PadOm1bh4T6AAVAOGAbm7y9+JdmzkqORIxcfYw0oDUafy4SikiYKRuB0pcjDkzYVs2ZfPsF4tefnaRLNLEhEPVecBKDg4mHXr1tGqVSsee+wx9uzZw8cff8zatWsZOHAg2dnZNS7eEygA1SKn4xR3pJVUfExw44qfkRYUWa+li+dYtu0Aw95JwzDgg1t6c3HnGLNLEhEPVJ2f3zVaYSw0NJT9+/fTqlUrZs+eTUpKCgCBgYEcOVLJb/vim6w2iGrrenUaenx/SZHreWhlQ9GxO9IK9sPWha5XWeEtStctKvuctI66I80H9Godxd/Pa8t7P29mzLTVzH6oEZHBuuBeRGquRgFo0KBB3H777Zx11lmsX7+eIUOGALB27Vri4+Nrsz5pqPzsx0d4yioqqPiOtNydkLvL9do0r8wBFmgUf/KIUeME3ZHWwKQM6sC89L1sys7nqW//5LXhSWaXJCJerEYBaNKkSfzzn/9kx44dfPnllzRu3BiAZcuWccMNN9RqgeJj7MHQPMn1KutoTvk70Y49FiQ/Gw5ucb0yvj/e3urnui3/xOuLGsXrjjQvFehv4+VrE/nr5F+ZvmIXl3aLZXDXWLPLEhEvpdvgK6BrgLzI4ewKnpGWDoW5Fbf3C3RNm514R1p4C1147SVemLmOyfM3ER1qZ/ZDFxAVopE+EXGp84ugZ86cSWhoKOeeey7gGhF6//336dKlC5MmTaJRI+9+fIICkJczDNdU2YkPjs3OgJKjFR8TEH7y9UVNu0CoHsHgaQpLHFwx8RfW7z3MFYnNmXjDWWaXJCIeos4DUPfu3XnhhRcYMmQIq1evpk+fPqSkpPDTTz/RqVMnPvzwwxoX7wkUgBoopwMObj15DaP9G05xR1r0yaEopgsEhNVr6VLeqp2HuPrtX3E4Dd6+sSdDujczuyQR8QB1HoBCQ0NZs2YN8fHxPPnkk6xZs4YvvviC5cuXM2TIEDIzM2tcvCdQAPIxJUWwf+MJd6T96QpLVPDtERAON3wK8efUd6VSxiuzM5j440aiQuzMfuh8okMDzC5JRExW57fB2+12CgoKAJg7dy4jRowAICoqitzcSq69EPFUfnbXqE5Ml/L7iwpgX0b50aLM1XB4L0y7A+5apLWJTHTfRe2Z8+de1mXm8cRXa3j7xp5YdB2XiFSRtSYHnXvuuaSkpDBhwgSWLFnifiTG+vXradmyZbXPN2nSJOLj4wkMDKRfv34sWbKk0rbTpk2jd+/eREZGEhISQlJSElOnTnV/vbi4mMcee4zu3bsTEhJC8+bNGTFiBLt3765+R8W32YOh+VmQ9H9wyTNw05dw33LXmka5O2HGw2ZX6NPsflZevjYRP6uFH9Zk8t2qPWaXJCJepEYB6K233sLPz48vvviCyZMn06JFCwB++OEHLr300mqd67PPPiMlJYXx48ezfPlyEhMTGTx4MFlZFT9wMyoqirFjx5KWlsaqVasYOXIkI0eOZNasWQAUFBSwfPlynnjiCZYvX860adPIyMjgL3/5S026KlJeQChc/R5YbLD6c1j9hdkV+bRuLSK496IEAJ74eg1ZeZVc5C4icgLTb4Pv168fffr04a233gLA6XQSFxfHfffdx+jRo6t0jp49ezJ06FAmTJhQ4deXLl1K37592bZtG61atTrt+XQNkJzWT8/BghcgMALu+tX1YFcxRbHDyZVvLeLPPbkM6hLDezf30lSYiI+qzs/vGo0AATgcDr788kueeeYZnnnmGaZPn47D4ajWOYqKili2bBnJycnHC7JaSU5OJi0t7bTHG4bBvHnzyMjI4Pzzz6+0XU5ODhaLhcjIyAq/XlhYSG5ubrmXyCmd/wi06OVaoPGru8DpNLsin+Vvs/LKdYn42yzM+XMvX63cZXZJIuIFahSANm7cSOfOnRkxYgTTpk1j2rRp3HTTTXTt2pVNmzZV+Tz79u3D4XAQE1P+wYYxMTGnvJMsJyeH0NBQ7HY7Q4cOZeLEiQwaNKjCtkePHuWxxx7jhhtuqDQNpqamEhER4X7FxcVVuQ/io2z+cM374B8MW36G3942uyKf1rlZOA9c3B6A8V+vZW+upsJE5NRqFIDuv/9+2rVrx44dO1i+fDnLly9n+/bttGnThvvvv7+2azxJWFgYK1euZOnSpTz77LOkpKQwf/78k9oVFxdz3XXXYRgGkydPrvR8Y8aMIScnx/3asWNHHVYvDUbjdjD4Wdf2vKdg71pz6/Fxd17Qju4tIsg9WsKYaavRIvcicio1CkALFizgxRdfJCoqyr2vcePGPP/88yxYsKDK54mOjsZms7F3795y+/fu3UtsbOXP+LFarSQkJJCUlMSoUaMYNmwYqamp5docCz/btm1jzpw5p5wLDAgIIDw8vNxLpEp6jYQOl4KjCL78OxRr5MEsfqVTYXablR/XZfHFsp1mlyQiHqxGASggIIC8vLyT9h8+fBi7verP5bHb7fTq1Yt5844/3dvpdDJv3jz69+9f5fM4nU4KCwvdfz8WfjZs2MDcuXPdD2sVqXUWC/xlomvF6Ky18GPFF+JL/egQE8ZDgzoA8PS3f7In54jJFYmIp6pRALr88su54447WLx4MYZhYBgGv/32G3feeWe1bzdPSUnh/fff56OPPiI9PZ277rqL/Px8Ro4cCcCIESMYM2aMu31qaipz5sxh8+bNpKen88orrzB16lRuuukmwBV+hg0bxu+//85//vMfHA4HmZmZZGZmUlRUVJPuipxaaFO40nUXI2mTXNcEiWn+fl4bkuIiySss4bEvNRUmIhWr0UrQb775Jrfccgv9+/fH398fcAWPK6+8ktdff71a5xo+fDjZ2dmMGzeOzMxMkpKSmDlzpvvC6O3bt2O1Hs9p+fn53H333ezcuZOgoCA6derEJ598wvDhwwHYtWsX33zzDQBJSUnl3uunn35i4MCBNemyyKl1vAx63QrLpsD0O0tXifbuhwJ7Kz+ba4HEIW8u5Of12Xy2dAfX9z398hci4lvOaB2gjRs3kp6eDkDnzp1JSEiotcLMpHWApEYKD8O758GBzdBtGAz7wOyKfNr7P2/m2RnphAb4MfPB82jZKNjskkSkjtXJw1BTUlKqXMCrr75a5baeSAFIamzn7/DBJWA44K8fQPdhZlfksxxOg+veTWPZtoOck9CYT/7WTwskijRwdfIw1BUrVlSpnf4HIz6tZW+44FGYnwrfpUBcP4jUulJmsFktvDSsB0PeXMiijfv5z+Lt3HR2a7PLEhEPYfqjMDyRRoDkjDhK4N+DYdfvEH8ejPgGrDVedF3O0L9/2cLT3/1JsN3GrAfPJy5KU2EiDVW9PApDRCph84Nr3nOtEr11Ifw2yeyKfNqtA+Lp2yaKgiIHj3zxB06nfucTEQUgkbrRuB0Mfs61Pe9pyFxjbj0+zGq18PKwRILtNn7bfICpv20zuyQR8QAKQCJ1pdet0OEy1yrR0+7QKtEmatU4mDGXdQLg+R/WsXVfvskViYjZdA1QBXQNkNSaw9kwuT/kZ0P/e48/O0zqndNpcNMHi/l1035aRAbRtkkIQf42Av1tBPnbCLLbCPC3urbL7Hfvsx/fF+hvI7Dsfj8bVqtuABExW53cBu9LFICkVmXMhP+6FupkxDfQ9gJz6/FhOw4UcNkbCzlcWFLr57b7WUvDkbVMSLId32cvv+/Y/sAyISrIXj50lQ1ngX42Au1W7Dar7rYVqYQC0BlSAJJa9+2DsOxDCG+hVaJNtm1/Pmt353K02MGRYgdHihwUljg5UuQ4vq/YQWGx0/31oyUO99ePHttf7KCoxFnv9VstnDwSZbdVHLrK7rPbCPSrIIi5w5f1hONt2DSqJV6mTtYBEpEzMPhZ1zPCDmyC70fBsH+bXZHPat04hNaNQ2rlXE6nwdGSMqHIHZJcAenY/qNlQtSx/WXbuUKWk6Purx//89g5HKV3rzkNKChyUFDkqJU+nIrdZi03SuUanbIRdMIIVWCZEFU2dB0PWdbSEazy04vHRrsC/DSqJfVPAUikPthD4Jr34YNBsOZL18XRPa41uyo5Q1arhWC7H8H2un+vYkeZMFVmFModltwhy1kmPJUNWU5XWCsXsk4OYoVlRrWKHE6KHE5yj9b+lGFZFgsVX3d1ihEsP6sFm9WCxWLBZrFgs7oW4rVZLVgtYHVvW7CW7rO5t13trRZLmXZVO+b4+1mwWDjevtLzlP697DkrOEYBsP4pAInUl5a94ILHYP5zrlGgVmdrlWipMn+bFX+blfBA/zp9H6fToLDEWW460B2SipwnTBOWD1euAFV+pOtIBUHs2HElpaNaRj2Oankqi6VsUKo4NFUevsqHKqv1hOBW9pzu85Q/Z9mvu89z7LxlwuCxkOmuwVI+iFotrl8MyoZB93nLhkqLhc7NwuneMsK0f3MFIJH6dN4o2DgHdi6Fr+7SKtHicaxWi2u6y26jrq9UK3YcD1SFJ0wjnjgFeOxarGMjWCVOA8NwPfPNYRgYhuHaduLaNgychivQOZwGTuPYi3J/dzgNnE5c25Uc4zj2XsfO4azgHKXHuc9T5pxVudL22PkdGOAjOfDuge0UgER8hs0Prn4X3jnPtUp02ltwzv1mVyViimOjWmF1PKplNqOy4FVZaHKWD2vHAp2jTOg7fh5KQ1n5AFfReWp0TGmd5UKmcUIdzorCIyf0tTQ4Gob7vdo2CTX1c1EAEqlvjdvBpanw7f3w4wRodyHEdje7KhGpI2WnnMRzaOxdxAw9R0DHIa5Vor/8u1aJFhGpZwpAImawWOCKNyGkCWSnu54XJiIi9UYBSMQsoU3gytInxf82CTbPN7UcERFfogAkYqYOg6H3ba7t6XfBkYPm1iMi4iMUgETMdskzENUO8nbDdylU6Z5ZERE5IwpAImY7tkq0xQZrp8Hqz82uSESkwVMAEvEELXvBwNGu7e8fhkPbza1HRKSBUwAS8RTnpkDLPlCY47oeyOkjy8GKiJhAAUjEU9j84Jr3wD8Etv3iWiVaRETqhAKQiCeJaguXPe/anjcBMlebW4+ISAOlACTiac66GTpdDs5irRItIlJHFIBEPI3FAle8ASFNS1eJfsrsikREGhwFIBFPFBJdZpXot2HTT+bWIyLSwCgAiXiqDpdA77+5tr+6CwoOmFuPiEgDogAk4skueQYaJ0DeHvheq0SLiNQWBSART2YPdt0ab/WDtdNh1f/MrkhEpEFQABLxdC16wQWlq0TP0CrRIiK1QQFIxBuc+xC07AuFuTD9Tq0SLSJyhhSARLyBzQ+ueRfsobBtEfw60eyKRES8mgKQiLeIaguXlq4S/eMzsGeVufWIiHgxBSARb3LWTcdXiZ72dyg+YnZFIiJeSQFIxJuUWyV6HczVKtEiIjWhACTibUKi4aq3XduLJ8OmH82tR0TECykAiXij9oOgz+2u7a/u1irRIiLVpAAk4q0GTYDG7V2rRH/3kFaJFhGpBgUgEW9VdpXoP7+CVZ+ZXZGIiNdQABLxZi16wsDSVaK/fxgObjO3HhERL6EAJOLtznkI4vpBUZ5WiRYRqSIFIBFvZ/ODq0tXid7+K/z6ptkViYh4PAUgkYYgqg1c9oJr+8dnYc8f5tYjIuLhFIBEGoqkG4+vEv2lVokWETkVBSCRhsJigSvehNAY2JcBc580uyIREY+lACTSkIQ0hiuPrRL9DmycZ249IiIeSgFIpKFpnwx9/u7a1irRIiIVUgASaYgGPQ3RHeBwJnz3oFaJFhE5gQKQSENUbpXor+GPT82uSETEoygAiTRUzc+CgWNc2zMegYNbTS1HRMSTKACJNGTnPgRxZ2uVaBGREygAiTRkVhtc8y7Yw2B7Gix6w+yKREQ8ggKQSEPXKP74KtE/PQu7V5pZjYiIR1AAEvEFSf8Hna8AZwlMu0OrRIuIz1MAEvEFFgtc/sbxVaLnjDe7IhERUykAifiKkMZwVekq0UvehY1zza1HRMRECkAiviQhGfre4dr+6h6tEi0iPksBSMTXJD91fJXobx/QKtEi4pNMD0CTJk0iPj6ewMBA+vXrx5IlSyptO23aNHr37k1kZCQhISEkJSUxderUk9pccsklNG7cGIvFwsqVK+u4ByJexh4M17zvWiU6/Rv4479mVyQiUu9MDUCfffYZKSkpjB8/nuXLl5OYmMjgwYPJysqqsH1UVBRjx44lLS2NVatWMXLkSEaOHMmsWbPcbfLz8zn33HN54YUX6qsbIt6neRJc+Lhre8ajWiVaRHyOxTDMG//u168fffr04a233gLA6XQSFxfHfffdx+jRo6t0jp49ezJ06FAmTJhQbv/WrVtp06YNK1asICkpqVp15ebmEhERQU5ODuHh4dU6VsRrOB0wZahrgcS4s2HkDNfCiSIiXqo6P79NGwEqKipi2bJlJCcnHy/GaiU5OZm0tLTTHm8YBvPmzSMjI4Pzzz//jGopLCwkNze33EukwbPa4Op3XKtE7/gNFr1udkUiIvXGtAC0b98+HA4HMTEx5fbHxMSQmZlZ6XE5OTmEhoZit9sZOnQoEydOZNCgQWdUS2pqKhEREe5XXFzcGZ1PxGs0iochL7q2f3oOdq8wtRwRkfpi+kXQ1RUWFsbKlStZunQpzz77LCkpKcyfP/+MzjlmzBhycnLcrx07dtROsSLeIPEG6PyX46tEFxWYXZGISJ3zM+uNo6Ojsdls7N27t9z+vXv3EhsbW+lxVquVhIQEAJKSkkhPTyc1NZWBAwfWuJaAgAACAgJqfLyIV7NY4Io3YMcS2Lce5o6HIS+ZXZWISJ0ybQTIbrfTq1cv5s2b597ndDqZN28e/fv3r/J5nE4nhYWFdVGiiO8IjiqzSvR7sEGrRItIw2baCBBASkoKt9xyC71796Zv3768/vrr5OfnM3LkSABGjBhBixYtSE1NBVzX6vTu3Zt27dpRWFjIjBkzmDp1KpMnT3af88CBA2zfvp3du3cDkJGRAUBsbOwpR5ZEfF7CxdD3H67HZHx9N9yV5np8hohIA2RqABo+fDjZ2dmMGzeOzMxMkpKSmDlzpvvC6O3bt2O1Hh+kys/P5+6772bnzp0EBQXRqVMnPvnkE4YPH+5u880337gDFMD1118PwPjx43nyySfrp2Mi3mrQU7B5vuuBqd89ANdNdU2RiYg0MKauA+SptA6Q+LTdK+FfyeAshivfhrNuNLsiEZEq8Yp1gETEQ5VdJfqHR+HAFlPLERGpCwpAInKycx6AVgOg6DBMv9O1arSISAOiACQiJztxlehfXjO7IhGRWqUAJCIVa9T6+HpA81Nh13Jz6xERqUUKQCJSucTrocuVWiVaRBocBSARqZzFApe/DmHNYP8GmDPO7IpERGqFApCInFrZVaKXvg8b5phbj4hILVAAEpHTa3cR9LvTtf31PZC/39x6RETOkAKQiFRN8pPQpBMc3gvf3g9aQ1VEvJgCkIhUjX8QXPM+WP1h3Xew4hOzKxIRqTEFIBGpumY94KKxru2Zo7VKtIh4LQUgEameAfeXWSX6H+AoMbsiEZFqUwASkeo5tkp0QDjsWAyLtEq0iHgfBSARqb5yq0Q/r1WiRcTrKACJSM30GA5drtIq0SLilRSARKRmLBa4/LUyq0Q/YXZFIiJVpgAkIjUXHAVXTXZtL/0XrJ9tbj0iIlWkACQiZ6bdhdDvLtf21/dA/j5z6xERqQIFIBE5c8njoUlnyM+Cbx/QKtEi4vEUgETkzPkHwV/LrhI91eyKREROSQFIRGpHbHe46J+u7R9Gw4HN5tYjInIKCkAiUnsG3Aetz4XifJimVaJFxHMpAIlI7bHa4OrJrlWidy6BX141uyIRkQopAIlI7YpsBUNedm3Pfx52LTO3HhGRCigAiUjt63EddL0aDEfpKtH5ZlckIlKOApCI1D6LBYa+CmHNYf9GmK1VokXEsygAiUjdCI5yXQ8E8PsHsH6WufWIiJShACQidaftQDj7btf21/dqlWgR8RgKQCJSty4us0r0N/drlWgR8QgKQCJSt/wDXatE2+yQ8T0s/9jsikREFIBEpB6UXSV65hjYv8ncekTE5ykAiUj96H8vxJ/nWiV6ulaJFhFzKQCJSP2w2uCqyRAQATuXwsJXzK5IRHyYApCI1J/IOBhaukr0ghdgp1aJFhFzKACJSP3qfi10+2vpKtF/1yrRImIKBSARqV8WCwx9BcJbwIFNMGus2RWJiA9SABKR+hfUCK5627W97EPImGluPSLicxSARMQcbQfC2fe4tr+5Fw5nm1qOiPgWBSARMc/F46BpF8jPhm+1SrSI1B8FIBExj38gXHNslegZsPwjsysSER+hACQi5ortBhc94dqe+bhWiRaReqEAJCLmK7tK9LQ7tEq0iNQ5BSARMZ/VCle/41oletfvsPBlsysSkQZOAUhEPENES9f6QAALXoSdv5tbj4g0aApAIuI5elwL3YYdXyW68LDZFYlIA6UAJCKeZejLpatEb4bZWiVaROqGApCIeJagRq6nxgMsmwIZP5hajog0TApAIuJ52l7gujMM4Ot74XCWufWISIOjACQinunicdC0KxTsg2/u0yrRIlKrFIBExDP5BcBfS1eJXj/TNR0mIlJLFIBExHPFdHWNBAHM0irRIlJ7FIBExLOdfU/pKtEFrlvjHcVmVyQiDYACkIh4tmOrRAdGwK5l8LNWiRaRM6cAJCKeL6IlDH3Vtf3zS1olWkTOmAKQiHiH7sOg+7VaJVpEaoUCkIh4jyEvQ3hL1yrRsx43uxoR8WIKQCLiPYIi4erJgAWWfwTrZphdkYh4KQUgEfEubc6HAaWrRH9zn1aJFpEaUQASEe9z0RMQ0821SvTX92qVaBGpNgUgEfE+fgFwzXuuVaI3zIJlH5pdkYh4GY8IQJMmTSI+Pp7AwED69evHkiVLKm07bdo0evfuTWRkJCEhISQlJTF16tRybQzDYNy4cTRr1oygoCCSk5PZsGFDXXdDROpTTFdIftK1PWss7Ntoajki4l1MD0CfffYZKSkpjB8/nuXLl5OYmMjgwYPJyqp4Xj8qKoqxY8eSlpbGqlWrGDlyJCNHjmTWrFnuNi+++CJvvvkm77zzDosXLyYkJITBgwdz9OjR+uqWiNSHfndBmwtcq0RPv0OrRItIlVkMw9zJ8379+tGnTx/eeustAJxOJ3Fxcdx3332MHj26Sufo2bMnQ4cOZcKECRiGQfPmzRk1ahQPP/wwADk5OcTExDBlyhSuv/76054vNzeXiIgIcnJyCA8Pr3nnRKTu5eyCyf3haA5c8BhcqNvjRXxVdX5+mzoCVFRUxLJly0hOTnbvs1qtJCcnk5aWdtrjDcNg3rx5ZGRkcP755wOwZcsWMjMzy50zIiKCfv36VXrOwsJCcnNzy71ExEtEtCizSvTLsGOpufWIiFcwNQDt27cPh8NBTExMuf0xMTFkZmZWelxOTg6hoaHY7XaGDh3KxIkTGTRoEID7uOqcMzU1lYiICPcrLi7uTLolIvWt+zDofp1WiRaRKjP9GqCaCAsLY+XKlSxdupRnn32WlJQU5s+fX+PzjRkzhpycHPdrx44dtVesiNSPIS+5Vok+uAVmjTG7GhHxcKYGoOjoaGw2G3v37i23f+/evcTGxlZ6nNVqJSEhgaSkJEaNGsWwYcNITU0FcB9XnXMGBAQQHh5e7iUiXiYo0vXUeCyw/GOtEi0ip2RqALLb7fTq1Yt58+a59zmdTubNm0f//v2rfB6n00lhYSEAbdq0ITY2ttw5c3NzWbx4cbXOKSJeqM15MOA+1/Y390Le3lO3FxGf5Wd2ASkpKdxyyy307t2bvn378vrrr5Ofn8/IkSMBGDFiBC1atHCP8KSmptK7d2/atWtHYWEhM2bMYOrUqUyePBkAi8XCgw8+yDPPPEP79u1p06YNTzzxBM2bN+eqq64yq5siUl8u+ids+gn2rnaFoP/7H1gsZlclIh7G9AA0fPhwsrOzGTduHJmZmSQlJTFz5kz3Rczbt2/Haj0+UJWfn8/dd9/Nzp07CQoKolOnTnzyyScMHz7c3ebRRx8lPz+fO+64g0OHDnHuuecyc+ZMAgMD671/IlLPjq0S/d5A2DAbfv839Pmb2VWJiIcxfR0gT6R1gEQagLS3XRdD+wXBnQshur3ZFYlIHfOadYBEROpMvztdq0SXHHHdGq9VokWkDAUgEWmYrFa4ajIERsDuFbDgRbMrEhEPogAkIg1XRAu4/HXX9sKXYUflD1oWEd+iACQiDVu3a6DHcDCcMO0OKMwzuyIR8QAKQCLS8A15CSLiXKtEz9Qq0SKiACQiviAw4vgq0SumwuovoOAAFB8F3Qgr4pNMXwdIRKRexJ8L59wPi96AL8usC2Sxgn8w+AeV/lm6bQ8p3RcE/mW23fuDyx9nD678PDZ/8/otIhVSABIR33HhWDiwGdbPAkeRa5/hhKLDrlddsfpVEqLKhqtjIep04aq0/YmBy2qru/pFGiAFIBHxHX4BMPwT17ajBIoLoPhI6Z9ltosKTrHvhPZF+aX7jkBxme2ifDAcrvdylkBhjutVV2wB1QxXwRUEqYrCVek+v0DX0gIiDYQCkIj4Jpsf2MIhsI5WezcM1+KLFYalMwhXJ7al9BomR6HrdfRQ3fQHKp7iq41w5Z4qtOu5bVJvFIBEROqCxQJ+dtcrKLJu3sMwoORoJeGqoILAVEmIOlXgKjl6/P2OtWV/3fTHfT1WFa6tstld034Wq+tPqx9YbKXbtuPbltKvWa1ltm0Vt3Wfw3rC+fyOv0+5c1grOJ9fxTVZrAp3HkYBSETEW1ksx0dQgqPq5j2czgrC0onh6jSBq9KpwtLRL2fpY0rq43osM9U4lFUSqModV9n5ThHmyp3vxPcuG/JOETDLhsaT3vs0NQWE190vB1WgACQiIpWzWiEg1PWqK47i8gGrqAqBy1lS+nK4gpN72+H6s9x2Sem2s8x2RW1rcL5yxzlO3U/DAY7TtPEl5zwIg54y7e0VgERExFw2f9errq7Hqi+GURqeKgpUjvLhy1lyirYlJ+x3VhC+qhHKKmxbUU2OE8JhXQTMMvX5BZj6cSkAiYiI1AaL5fjUkHg83dMoIiIiPkcBSERERHyOApCIiIj4HAUgERER8TkKQCIiIuJzFIBERETE5ygAiYiIiM9RABIRERGfowAkIiIiPkcBSERERHyOApCIiIj4HAUgERER8TkKQCIiIuJzFIBERETE5/iZXYAnMgwDgNzcXJMrERERkao69nP72M/xU1EAqkBeXh4AcXFxJlciIiIi1ZWXl0dERMQp21iMqsQkH+N0Otm9ezdhYWFYLJZaPXdubi5xcXHs2LGD8PDwWj23J1D/vF9D76P65/0aeh/Vv5ozDIO8vDyaN2+O1Xrqq3w0AlQBq9VKy5Yt6/Q9wsPDG+R/2Meof96vofdR/fN+Db2P6l/NnG7k5xhdBC0iIiI+RwFIREREfI4CUD0LCAhg/PjxBAQEmF1KnVD/vF9D76P65/0aeh/Vv/qhi6BFRETE52gESERERHyOApCIiIj4HAUgERER8TkKQCIiIuJzFIDqwKRJk4iPjycwMJB+/fqxZMmSU7b//PPP6dSpE4GBgXTv3p0ZM2bUU6U1U53+TZkyBYvFUu4VGBhYj9VWz88//8wVV1xB8+bNsVgsfPXVV6c9Zv78+fTs2ZOAgAASEhKYMmVKnddZU9Xt3/z580/6/CwWC5mZmfVTcDWlpqbSp08fwsLCaNq0KVdddRUZGRmnPc5bvgdr0j9v+x6cPHkyPXr0cC+S179/f3744YdTHuMtnx9Uv3/e9vmd6Pnnn8disfDggw+esp0Zn6ECUC377LPPSElJYfz48SxfvpzExEQGDx5MVlZWhe1//fVXbrjhBv72t7+xYsUKrrrqKq666irWrFlTz5VXTXX7B67VPvfs2eN+bdu2rR4rrp78/HwSExOZNGlSldpv2bKFoUOHcuGFF7Jy5UoefPBBbr/9dmbNmlXHldZMdft3TEZGRrnPsGnTpnVU4ZlZsGAB99xzD7/99htz5syhuLiYSy65hPz8/EqP8abvwZr0D7zre7Bly5Y8//zzLFu2jN9//52LLrqIK6+8krVr11bY3ps+P6h+/8C7Pr+yli5dyrvvvkuPHj1O2c60z9CQWtW3b1/jnnvucf/d4XAYzZs3N1JTUytsf9111xlDhw4tt69fv37GP/7xjzqts6aq278PP/zQiIiIqKfqahdgTJ8+/ZRtHn30UaNr167l9g0fPtwYPHhwHVZWO6rSv59++skAjIMHD9ZLTbUtKyvLAIwFCxZU2sbbvgfLqkr/vPl78JhGjRoZ//rXvyr8mjd/fsecqn/e+vnl5eUZ7du3N+bMmWNccMEFxgMPPFBpW7M+Q40A1aKioiKWLVtGcnKye5/VaiU5OZm0tLQKj0lLSyvXHmDw4MGVtjdTTfoHcPjwYVq3bk1cXNxpf9PxNt70+Z2JpKQkmjVrxqBBg1i0aJHZ5VRZTk4OAFFRUZW28ebPsCr9A+/9HnQ4HHz66afk5+fTv3//Ctt48+dXlf6Bd35+99xzD0OHDj3ps6mIWZ+hAlAt2rdvHw6Hg5iYmHL7Y2JiKr1mIjMzs1rtzVST/nXs2JF///vffP3113zyySc4nU4GDBjAzp0766PkOlfZ55ebm8uRI0dMqqr2NGvWjHfeeYcvv/ySL7/8kri4OAYOHMjy5cvNLu20nE4nDz74IOeccw7dunWrtJ03fQ+WVdX+eeP34OrVqwkNDSUgIIA777yT6dOn06VLlwrbeuPnV53+eePn9+mnn7J8+XJSU1Or1N6sz1BPg5c61b9//3K/2QwYMIDOnTvz7rvvMmHCBBMrk6ro2LEjHTt2dP99wIABbNq0iddee42pU6eaWNnp3XPPPaxZs4ZffvnF7FLqRFX7543fgx07dmTlypXk5OTwxRdfcMstt7BgwYJKQ4K3qU7/vO3z27FjBw888ABz5szx+Iu1FYBqUXR0NDabjb1795bbv3fvXmJjYys8JjY2tlrtzVST/p3I39+fs846i40bN9ZFifWuss8vPDycoKAgk6qqW3379vX4UHHvvffy3Xff8fPPP9OyZctTtvWm78FjqtO/E3nD96DdbichIQGAXr16sXTpUt544w3efffdk9p64+dXnf6dyNM/v2XLlpGVlUXPnj3d+xwOBz///DNvvfUWhYWF2Gy2cseY9RlqCqwW2e12evXqxbx589z7nE4n8+bNq3R+t3///uXaA8yZM+eU88FmqUn/TuRwOFi9ejXNmjWrqzLrlTd9frVl5cqVHvv5GYbBvffey/Tp0/nxxx9p06bNaY/xps+wJv07kTd+DzqdTgoLCyv8mjd9fpU5Vf9O5Omf38UXX8zq1atZuXKl+9W7d29uvPFGVq5ceVL4ARM/wzq9xNoHffrpp0ZAQIAxZcoU488//zTuuOMOIzIy0sjMzDQMwzBuvvlmY/To0e72ixYtMvz8/IyXX37ZSE9PN8aPH2/4+/sbq1evNqsLp1Td/j311FPGrFmzjE2bNhnLli0zrr/+eiMwMNBYu3atWV04pby8PGPFihXGihUrDMB49dVXjRUrVhjbtm0zDMMwRo8ebdx8883u9ps3bzaCg4ONRx55xEhPTzcmTZpk2Gw2Y+bMmWZ14ZSq27/XXnvN+Oqrr4wNGzYYq1evNh544AHDarUac+fONasLp3TXXXcZERERxvz58409e/a4XwUFBe423vw9WJP+edv34OjRo40FCxYYW7ZsMVatWmWMHj3asFgsxuzZsw3D8O7PzzCq3z9v+/wqcuJdYJ7yGSoA1YGJEycarVq1Mux2u9G3b1/jt99+c3/tggsuMG655ZZy7f/3v/8ZHTp0MOx2u9G1a1fj+++/r+eKq6c6/XvwwQfdbWNiYowhQ4YYy5cvN6Hqqjl22/eJr2N9uuWWW4wLLrjgpGOSkpIMu91utG3b1vjwww/rve6qqm7/XnjhBaNdu3ZGYGCgERUVZQwcOND48ccfzSm+CirqG1DuM/Hm78Ga9M/bvgdvu+02o3Xr1obdbjeaNGliXHzxxe5wYBje/fkZRvX7522fX0VODECe8hlaDMMw6naMSURERMSz6BogERER8TkKQCIiIuJzFIBERETE5ygAiYiIiM9RABIRERGfowAkIiIiPkcBSERERHyOApCIiIj4HAUgEZEqmD9/PhaLhUOHDpldiojUAgUgERER8TkKQCIiIuJzFIBExCs4nU5SU1Np06YNQUFBJCYm8sUXXwDHp6e+//57evToQWBgIGeffTZr1qwpd44vv/ySrl27EhAQQHx8PK+88kq5rxcWFvLYY48RFxdHQEAACQkJfPDBB+XaLFu2jN69exMcHMyAAQPIyMio246LSJ1QABIRr5CamsrHH3/MO++8w9q1a3nooYe46aabWLBggbvNI488wiuvvMLSpUtp0qQJV1xxBcXFxYAruFx33XVcf/31rF69mieffJInnniCKVOmuI8fMWIE//3vf3nzzTdJT0/n3XffJTQ0tFwdY8eO5ZVXXuH333/Hz8+P2267rV76LyK1S0+DFxGPV1hYSFRUFHPnzqV///7u/bfffjsFBQXccccdXHjhhXz66acMHz4cgAMHDtCyZUumTJnCddddx4033kh2djazZ892H//oo4/y/fffs3btWtavX0/Hjh2ZM2cOycnJJ9Uwf/58LrzwQubOncvFF18MwIwZMxg6dChHjhwhMDCwjv8VRKQ2aQRIRDzexo0bKSgoYNCgQYSGhrpfH3/8MZs2bXK3KxuOoqKi6NixI+np6QCkp6dzzjnnlDvvOeecw4YNG3A4HKxcuRKbzcYFF1xwylp69Ojh3m7WrBkAWVlZZ9xHEalffmYXICJyOocPHwbg+++/p0WLFuW+FhAQUC4E1VRQUFCV2vn7+7u3LRYL4Lo+SUS8i0aARMTjdenShYCAALZv305CQkK5V1xcnLvdb7/95t4+ePAg69evp3PnzgB07tyZRYsWlTvvokWL6NChAzabje7du+N0OstdUyQiDZdGgETE44WFhfHwww/z0EMP4XQ6Offcc8nJyWHRokWEh4fTunVrAJ5++mkaN25MTEwMY8eOJTo6mquuugqAUaNG0adPHyZMmMDw4cNJS0vjrbfe4u233wYgPj6eW265hdtuu40333yTxMREtm3bRlZWFtddd51ZXReROqIAJCJeYcKECTRp0oTU1FQ2b95MZGQkPXv25PHHH3dPQT3//PM88MADbNiwgaSkJL799lvsdjsAPXv25H//+x/jxo1jwoQJNGvWjKeffppbb73V/R6TJ0/m8ccf5+6772b//v20atWKxx9/3Izuikgd011gIuL1jt2hdfDgQSIjI80uR0S8gK4BEhEREZ+jACQiIiI+R1NgIiIi4nM0AiQiIiI+RwFIREREfI4CkIiIiPgcBSARERHxOQpAIiIi4nMUgERERMTnKACJiIiIz1EAEhEREZ/z/wHknvOoOHOY9QAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lr: float = 4e-2\n",
    "n_epoch: int = 3\n",
    "n_splits: int = 3\n",
    "batch_size: int = 512\n",
    "verbose: bool = True\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "if dataset.empty:\n",
    "    raise ValueError('Training data is inadequate.')\n",
    "dataset['tensor'] = dataset.progress_apply(lambda x: lineToTensor(list(zip([x['t_history']], [x['r_history']]))[0]), axis=1)\n",
    "dataset['group'] = dataset['r_history'] + dataset['t_history']\n",
    "print(\"Tensorized!\")\n",
    "\n",
    "n_pre_train_groups = len(dataset[dataset['i'] == 2]['group'].unique())\n",
    "if n_pre_train_groups < n_splits:\n",
    "    print(\"Not enough groups for pre-training. Splitting into {} folds.\".format(n_pre_train_groups))\n",
    "    n_splits = n_pre_train_groups\n",
    "\n",
    "w = []\n",
    "plots = []\n",
    "if n_splits > 1:\n",
    "    sgkf = StratifiedGroupKFold(n_splits=n_splits)\n",
    "    for train_index, test_index in sgkf.split(dataset, dataset['i'], dataset['group']):\n",
    "        print(\"TRAIN:\", len(train_index), \"TEST:\",  len(test_index))\n",
    "        train_set = dataset.iloc[train_index].copy()\n",
    "        test_set = dataset.iloc[test_index].copy()\n",
    "        trainer = Trainer(train_set, test_set, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "        w.append(trainer.train(verbose=verbose))\n",
    "        plots.append(trainer.plot())\n",
    "else:\n",
    "    trainer = Trainer(dataset, dataset, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "    w.append(trainer.train(verbose=verbose))\n",
    "    plots.append(trainer.plot())\n",
    "\n",
    "w = np.array(w)\n",
    "avg_w = np.round(np.mean(w, axis=0), 4)\n",
    "w = avg_w.tolist()\n",
    "print(\"\\nTraining finished!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.5175, 2.0482, 4.8785, -1.9606, -1.8261, 0.05, 1.4788, -0.2206, 0.9072, 2.4097, -0.0214, 0.3333, 0.9109]\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "\n",
      "first rating: 1\n",
      "rating history: 1,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,2d,3d,6d,10d,18d,1.0m,1.6m,2.6m,4.1m,6.2m\n",
      "difficulty history: 0,8.8,8.6,8.4,8.2,8.1,7.9,7.8,7.6,7.5,7.3\n",
      "\n",
      "first rating: 2\n",
      "rating history: 2,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,4d,9d,19d,1.2m,2.3m,4.0m,6.8m,10.9m,1.4y,2.1y\n",
      "difficulty history: 0,6.8,6.7,6.6,6.6,6.5,6.4,6.3,6.2,6.2,6.1\n",
      "\n",
      "first rating: 3\n",
      "rating history: 3,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,6d,16d,1.3m,2.7m,5.4m,9.8m,1.4y,2.3y,3.6y,5.5y\n",
      "difficulty history: 0,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9\n",
      "\n",
      "first rating: 4\n",
      "rating history: 4,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,8d,25d,2.2m,5.0m,10.3m,1.6y,2.8y,4.8y,7.6y,11.6y\n",
      "difficulty history: 0,2.9,3.0,3.1,3.2,3.3,3.4,3.4,3.5,3.6,3.6\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(w)\n",
    "\n",
    "class Collection:\n",
    "    def __init__(self, w: List[float]) -> None:\n",
    "        self.model = FSRS(w)\n",
    "        self.model.eval()\n",
    "\n",
    "    def predict(self, t_history: str, r_history: str):\n",
    "        with torch.no_grad():\n",
    "            line_tensor = lineToTensor(list(zip([t_history], [r_history]))[0]).unsqueeze(1)\n",
    "            output_t = self.model(line_tensor)\n",
    "            return output_t[-1][0]\n",
    "\n",
    "    def batch_predict(self, dataset):\n",
    "        fast_dataset = RevlogDataset(dataset)\n",
    "        with torch.no_grad():\n",
    "            outputs, _ = self.model(fast_dataset.x_train.transpose(0, 1))\n",
    "            stabilities, difficulties = outputs[fast_dataset.seq_len-1, torch.arange(len(fast_dataset))].transpose(0, 1)\n",
    "            return stabilities.tolist(), difficulties.tolist()\n",
    "        \n",
    "requestRetention = 0.9\n",
    "\n",
    "my_collection = Collection(w)\n",
    "preview_text = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "for first_rating in (1,2,3,4):\n",
    "    preview_text += f'\\nfirst rating: {first_rating}\\n'\n",
    "    t_history = \"0\"\n",
    "    d_history = \"0\"\n",
    "    r_history = f\"{first_rating}\"  # the first rating of the new card\n",
    "    # print(\"stability, difficulty, lapses\")\n",
    "    for i in range(10):\n",
    "        states = my_collection.predict(t_history, r_history)\n",
    "        # print('{0:9.2f} {1:11.2f} {2:7.0f}'.format(\n",
    "            # *list(map(lambda x: round(float(x), 4), states))))\n",
    "        next_t = max(round(float(np.log(requestRetention)/np.log(0.9) * states[0])), 1)\n",
    "        difficulty = round(float(states[1]), 1)\n",
    "        t_history += f',{int(next_t)}'\n",
    "        d_history += f',{difficulty}'\n",
    "        r_history += f\",3\"\n",
    "    preview_text += f\"rating history: {r_history}\\n\"\n",
    "    preview_text += \"interval history: \" + \",\".join([f\"{ivl}d\" if ivl < 30 else f\"{ivl / 30:.1f}m\" if ivl < 365 else f\"{ivl / 365:.1f}y\" for ivl in map(int, t_history.split(','))]) + \"\\n\"\n",
    "    preview_text += f\"difficulty history: {d_history}\\n\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([5.6139, 4.8785])\n",
      "tensor([16.0674,  4.8785])\n",
      "tensor([38.1855,  4.8785])\n",
      "tensor([81.5843,  4.8785])\n",
      "tensor([160.7870,   4.8785])\n",
      "tensor([11.2207,  8.3481])\n",
      "tensor([ 3.2688, 10.0000])\n",
      "tensor([4.4787, 9.7439])\n",
      "tensor([6.2754, 9.5007])\n",
      "tensor([9.1613, 9.2695])\n",
      "tensor([13.6479,  9.0500])\n",
      "tensor([20.7208,  8.8414])\n",
      "rating history: 3,3,3,3,3,1,1,3,3,3,3,3\n",
      "interval history: 0,6,16,38,82,161,11,3,4,6,9,14,21\n",
      "difficulty history: 0,4.9,4.9,4.9,4.9,4.9,8.3,10.0,9.7,9.5,9.3,9.0,8.8\n"
     ]
    }
   ],
   "source": [
    "test_rating_sequence = \"3,3,3,3,3,1,1,3,3,3,3,3\"\n",
    "requestRetention = 0.9  # recommended setting: 0.8 ~ 0.9\n",
    "easyBonus = 1.3\n",
    "hardInterval = 1.2\n",
    "\n",
    "t_history = \"0\"\n",
    "d_history = \"0\"\n",
    "for i in range(len(test_rating_sequence.split(','))):\n",
    "    rating = test_rating_sequence[2*i]\n",
    "    last_t = int(t_history.split(',')[-1])\n",
    "    r_history = test_rating_sequence[:2*i+1]\n",
    "    states = my_collection.predict(t_history, r_history)\n",
    "    print(states)\n",
    "    next_t = max(1,round(float(np.log(requestRetention)/np.log(0.9) * states[0])))\n",
    "    if rating == '4':\n",
    "        next_t = round(next_t * easyBonus)\n",
    "    elif rating == '2':\n",
    "        next_t = round(last_t * hardInterval)\n",
    "    t_history += f',{int(next_t)}'\n",
    "    difficulty = round(float(states[1]), 1)\n",
    "    d_history += f',{difficulty}'\n",
    "preview_text = f\"rating history: {test_rating_sequence}\\n\"\n",
    "preview_text += f\"interval history: {t_history}\\n\"\n",
    "preview_text += f\"difficulty history: {d_history}\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss before: 0.3371, loss after: 0.3101, improvement: 0.0270\n"
     ]
    }
   ],
   "source": [
    "my_collection = Collection(init_w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_before = dataset['log_loss'].mean()\n",
    "\n",
    "my_collection = Collection(w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_after = dataset['log_loss'].mean()\n",
    "\n",
    "tmp = dataset.copy()\n",
    "tmp['stability'] = tmp['stability'].map(lambda x: round(x, 2))\n",
    "tmp['difficulty'] = tmp['difficulty'].map(lambda x: round(x, 2))\n",
    "tmp['p'] = tmp['p'].map(lambda x: round(x, 2))\n",
    "tmp['log_loss'] = tmp['log_loss'].map(lambda x: round(x, 2))\n",
    "tmp.rename(columns={\"r\": \"grade\", \"p\": \"retrievability\"}, inplace=True)\n",
    "tmp[['id', 'cid', 'review_date', 'r_history', 't_history', 'delta_t', 'grade', 'stability', 'difficulty', 'retrievability', 'log_loss']].to_csv(\"./evaluation.tsv\", sep='\\t', index=False)\n",
    "del tmp\n",
    "print(f\"loss before: {loss_before:.4f}, loss after: {loss_after:.4f}, improvement: {loss_before - loss_after:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-squared: 0.9342\n",
      "RMSE: 0.0180\n",
      "[0.10123924 0.88748061]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Last rating: 1\n",
      "R-squared: 0.0997\n",
      "RMSE: 0.0503\n",
      "[0.35905057 0.57998195]\n",
      "\n",
      "Last rating: 2\n",
      "R-squared: -0.6784\n",
      "RMSE: 0.0953\n",
      "[-0.55756963  1.50702818]\n",
      "\n",
      "Last rating: 3\n",
      "R-squared: 0.9303\n",
      "RMSE: 0.0205\n",
      "[0.04162002 0.96619094]\n",
      "\n",
      "Last rating: 4\n",
      "R-squared: -0.3844\n",
      "RMSE: 0.0360\n",
      "[0.48503482 0.5067021 ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1200 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code from https://github.com/papousek/duolingo-halflife-regression/blob/master/evaluation.py\n",
    "def load_brier(predictions, real, bins=20):\n",
    "    counts = np.zeros(bins)\n",
    "    correct = np.zeros(bins)\n",
    "    prediction = np.zeros(bins)\n",
    "    for p, r in zip(predictions, real):\n",
    "        bin = min(int(p * bins), bins - 1)\n",
    "        counts[bin] += 1\n",
    "        correct[bin] += r\n",
    "        prediction[bin] += p\n",
    "    np.seterr(invalid='ignore')\n",
    "    prediction_means = prediction / counts\n",
    "    prediction_means[np.isnan(prediction_means)] = ((np.arange(bins) + 0.5) / bins)[np.isnan(prediction_means)]\n",
    "    correct_means = correct / counts\n",
    "    correct_means[np.isnan(correct_means)] = 0\n",
    "    size = len(predictions)\n",
    "    answer_mean = sum(correct) / size\n",
    "    return {\n",
    "        \"reliability\": sum(counts * (correct_means - prediction_means) ** 2) / size,\n",
    "        \"resolution\": sum(counts * (correct_means - answer_mean) ** 2) / size,\n",
    "        \"uncertainty\": answer_mean * (1 - answer_mean),\n",
    "        \"detail\": {\n",
    "            \"bin_count\": bins,\n",
    "            \"bin_counts\": list(counts),\n",
    "            \"bin_prediction_means\": list(prediction_means),\n",
    "            \"bin_correct_means\": list(correct_means),\n",
    "        }\n",
    "    }\n",
    "\n",
    "\n",
    "def plot_brier(predictions, real, bins=20):\n",
    "    brier = load_brier(predictions, real, bins=bins)\n",
    "    bin_prediction_means = brier['detail']['bin_prediction_means']\n",
    "    bin_correct_means = brier['detail']['bin_correct_means']\n",
    "    bin_counts = brier['detail']['bin_counts']\n",
    "    r2 = r2_score(bin_correct_means, bin_prediction_means, sample_weight=bin_counts)\n",
    "    rmse = mean_squared_error(bin_correct_means, bin_prediction_means, sample_weight=bin_counts, squared=False)\n",
    "    print(f\"R-squared: {r2:.4f}\")\n",
    "    print(f\"RMSE: {rmse:.4f}\")\n",
    "    ax = plt.gca()\n",
    "    ax.set_xlim([0, 1])\n",
    "    ax.set_ylim([0, 1])\n",
    "    plt.grid(True)\n",
    "    fit_wls = sm.WLS(bin_correct_means, sm.add_constant(bin_prediction_means), weights=bin_counts).fit()\n",
    "    print(fit_wls.params)\n",
    "    y_regression = [fit_wls.params[0] + fit_wls.params[1]*x for x in bin_prediction_means]\n",
    "    plt.plot(bin_prediction_means, y_regression, label='Weighted Least Squares Regression', color=\"green\")\n",
    "    plt.plot(bin_prediction_means, bin_correct_means, label='Actual Calibration', color=\"#1f77b4\")\n",
    "    plt.plot((0, 1), (0, 1), label='Perfect Calibration', color=\"#ff7f0e\")\n",
    "    bin_count = brier['detail']['bin_count']\n",
    "    counts = np.array(bin_counts)\n",
    "    bins = (np.arange(bin_count) + 0.5) / bin_count\n",
    "    plt.legend(loc='upper center')\n",
    "    plt.xlabel('Predicted R')\n",
    "    plt.ylabel('Actual R')\n",
    "    plt.twinx()\n",
    "    plt.ylabel('Number of reviews')\n",
    "    plt.bar(bins, counts, width=(0.8 / bin_count), ec='k', lw=.2, alpha=0.5, label='Number of reviews')\n",
    "    plt.legend(loc='lower center')\n",
    "\n",
    "\n",
    "plot_brier(dataset['p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "plt.figure(figsize=(16, 12))\n",
    "for last_rating in (\"1\",\"2\",\"3\",\"4\"):\n",
    "    plt.subplot(2, 2, int(last_rating))\n",
    "    print(f\"\\nLast rating: {last_rating}\")\n",
    "    plot_brier(dataset[dataset['r_history'].str.endswith(last_rating)]['p'], dataset[dataset['r_history'].str.endswith(last_rating)]['y'], bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def to_percent(temp, position):\n",
    "    return '%1.0f' % (100 * temp) + '%'\n",
    "\n",
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "stability_calibration = pd.DataFrame(columns=['stability', 'predicted_retention', 'actual_retention'])\n",
    "stability_calibration = dataset[['stability', 'p', 'y']].copy()\n",
    "stability_calibration['bin'] = stability_calibration['stability'].map(lambda x: math.pow(1.2, math.floor(math.log(x, 1.2))))\n",
    "stability_group = stability_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=stability_group.index, height=stability_group['y'], width=stability_group.index / 5.5,\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Stability (days)\")\n",
    "ax1.semilogx()\n",
    "lns.append(lns1)\n",
    "\n",
    "stability_group = stability_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(stability_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(stability_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "difficulty_calibration = pd.DataFrame(columns=['difficulty', 'predicted_retention', 'actual_retention'])\n",
    "difficulty_calibration = dataset[['difficulty', 'p', 'y']].copy()\n",
    "difficulty_calibration['bin'] = difficulty_calibration['difficulty'].map(round)\n",
    "difficulty_group = difficulty_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=difficulty_group.index, height=difficulty_group['y'],\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Difficulty\")\n",
    "lns.append(lns1)\n",
    "\n",
    "difficulty_group = difficulty_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(difficulty_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(difficulty_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_bcb49_row0_col0, #T_bcb49_row0_col1, #T_bcb49_row0_col2, #T_bcb49_row0_col3, #T_bcb49_row0_col4, #T_bcb49_row0_col5, #T_bcb49_row1_col0, #T_bcb49_row1_col1, #T_bcb49_row1_col2, #T_bcb49_row1_col3, #T_bcb49_row1_col4, #T_bcb49_row1_col5, #T_bcb49_row2_col0, #T_bcb49_row2_col1, #T_bcb49_row2_col2, #T_bcb49_row2_col3, #T_bcb49_row2_col4, #T_bcb49_row3_col0, #T_bcb49_row3_col1, #T_bcb49_row3_col2, #T_bcb49_row3_col3, #T_bcb49_row4_col0, #T_bcb49_row4_col1, #T_bcb49_row4_col2, #T_bcb49_row5_col0, #T_bcb49_row5_col1, #T_bcb49_row5_col2, #T_bcb49_row6_col0, #T_bcb49_row6_col2, #T_bcb49_row7_col2, #T_bcb49_row8_col2, #T_bcb49_row13_col6, #T_bcb49_row14_col2, #T_bcb49_row14_col5, #T_bcb49_row14_col6, #T_bcb49_row15_col2, #T_bcb49_row15_col3, #T_bcb49_row15_col4, #T_bcb49_row15_col5, #T_bcb49_row15_col6, #T_bcb49_row16_col0, #T_bcb49_row16_col2, #T_bcb49_row16_col3, #T_bcb49_row16_col4, #T_bcb49_row16_col5, #T_bcb49_row16_col6 {\n",
       "  background-color: #000000;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row0_col6, #T_bcb49_row1_col6, #T_bcb49_row5_col4, #T_bcb49_row6_col4, #T_bcb49_row8_col1, #T_bcb49_row14_col4 {\n",
       "  background-color: #c9c9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row2_col5, #T_bcb49_row10_col4 {\n",
       "  background-color: #ffbdbd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row2_col6 {\n",
       "  background-color: #c5c5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row3_col4, #T_bcb49_row8_col5 {\n",
       "  background-color: #ffdddd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row3_col5 {\n",
       "  background-color: #8989ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row3_col6, #T_bcb49_row9_col1, #T_bcb49_row12_col1 {\n",
       "  background-color: #e9e9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row4_col3 {\n",
       "  background-color: #ff8585;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row4_col4, #T_bcb49_row7_col3, #T_bcb49_row11_col4 {\n",
       "  background-color: #f5f5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row4_col5, #T_bcb49_row9_col2 {\n",
       "  background-color: #fff1f1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row4_col6 {\n",
       "  background-color: #ededff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row5_col3, #T_bcb49_row12_col2 {\n",
       "  background-color: #f1f1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row5_col5 {\n",
       "  background-color: #7575ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row5_col6 {\n",
       "  background-color: #ffe5e5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row6_col1, #T_bcb49_row6_col3, #T_bcb49_row13_col2 {\n",
       "  background-color: #e5e5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row6_col5, #T_bcb49_row9_col0, #T_bcb49_row10_col3 {\n",
       "  background-color: #cdcdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row6_col6, #T_bcb49_row9_col5, #T_bcb49_row12_col4 {\n",
       "  background-color: #ffd5d5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row7_col0 {\n",
       "  background-color: #ddddff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row7_col1, #T_bcb49_row7_col5, #T_bcb49_row8_col0, #T_bcb49_row13_col1 {\n",
       "  background-color: #d9d9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row7_col4, #T_bcb49_row12_col5 {\n",
       "  background-color: #ffeded;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row7_col6 {\n",
       "  background-color: #ff9999;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row8_col3 {\n",
       "  background-color: #ff9d9d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row8_col4, #T_bcb49_row9_col4 {\n",
       "  background-color: #fff5f5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row8_col6 {\n",
       "  background-color: #ff7d7d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row9_col3, #T_bcb49_row10_col5 {\n",
       "  background-color: #ffb5b5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row9_col6 {\n",
       "  background-color: #ff3535;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row10_col0 {\n",
       "  background-color: #bdbdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row10_col1 {\n",
       "  background-color: #d1d1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row10_col2 {\n",
       "  background-color: #fff9f9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row10_col6 {\n",
       "  background-color: #ff2525;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row11_col0, #T_bcb49_row14_col0 {\n",
       "  background-color: #c1c1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row11_col1 {\n",
       "  background-color: #ffe9e9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row11_col2 {\n",
       "  background-color: #ffd9d9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row11_col3 {\n",
       "  background-color: #ff9191;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row11_col5 {\n",
       "  background-color: #ffc5c5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row11_col6 {\n",
       "  background-color: #ff6161;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row12_col0 {\n",
       "  background-color: #adadff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row12_col3 {\n",
       "  background-color: #ff7575;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row12_col6 {\n",
       "  background-color: #f20000;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row13_col0 {\n",
       "  background-color: #d5d5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row13_col3 {\n",
       "  background-color: #ff6969;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row13_col4 {\n",
       "  background-color: #fdfdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row13_col5, #T_bcb49_row16_col1 {\n",
       "  background-color: #8585ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row14_col1 {\n",
       "  background-color: #a5a5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row14_col3 {\n",
       "  background-color: #ffb9b9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_bcb49_row15_col0 {\n",
       "  background-color: #7d7dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_bcb49_row15_col1 {\n",
       "  background-color: #7171ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_bcb49\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >d_bin</th>\n",
       "      <th id=\"T_bcb49_level0_col0\" class=\"col_heading level0 col0\" >3</th>\n",
       "      <th id=\"T_bcb49_level0_col1\" class=\"col_heading level0 col1\" >5</th>\n",
       "      <th id=\"T_bcb49_level0_col2\" class=\"col_heading level0 col2\" >6</th>\n",
       "      <th id=\"T_bcb49_level0_col3\" class=\"col_heading level0 col3\" >7</th>\n",
       "      <th id=\"T_bcb49_level0_col4\" class=\"col_heading level0 col4\" >8</th>\n",
       "      <th id=\"T_bcb49_level0_col5\" class=\"col_heading level0 col5\" >9</th>\n",
       "      <th id=\"T_bcb49_level0_col6\" class=\"col_heading level0 col6\" >10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >s_bin</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row0\" class=\"row_heading level0 row0\" >0.710000</th>\n",
       "      <td id=\"T_bcb49_row0_col0\" class=\"data row0 col0\" ></td>\n",
       "      <td id=\"T_bcb49_row0_col1\" class=\"data row0 col1\" ></td>\n",
       "      <td id=\"T_bcb49_row0_col2\" class=\"data row0 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row0_col3\" class=\"data row0 col3\" ></td>\n",
       "      <td id=\"T_bcb49_row0_col4\" class=\"data row0 col4\" ></td>\n",
       "      <td id=\"T_bcb49_row0_col5\" class=\"data row0 col5\" ></td>\n",
       "      <td id=\"T_bcb49_row0_col6\" class=\"data row0 col6\" >-2.04%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row1\" class=\"row_heading level0 row1\" >1.000000</th>\n",
       "      <td id=\"T_bcb49_row1_col0\" class=\"data row1 col0\" ></td>\n",
       "      <td id=\"T_bcb49_row1_col1\" class=\"data row1 col1\" ></td>\n",
       "      <td id=\"T_bcb49_row1_col2\" class=\"data row1 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row1_col3\" class=\"data row1 col3\" ></td>\n",
       "      <td id=\"T_bcb49_row1_col4\" class=\"data row1 col4\" ></td>\n",
       "      <td id=\"T_bcb49_row1_col5\" class=\"data row1 col5\" ></td>\n",
       "      <td id=\"T_bcb49_row1_col6\" class=\"data row1 col6\" >-2.08%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row2\" class=\"row_heading level0 row2\" >1.400000</th>\n",
       "      <td id=\"T_bcb49_row2_col0\" class=\"data row2 col0\" ></td>\n",
       "      <td id=\"T_bcb49_row2_col1\" class=\"data row2 col1\" ></td>\n",
       "      <td id=\"T_bcb49_row2_col2\" class=\"data row2 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row2_col3\" class=\"data row2 col3\" ></td>\n",
       "      <td id=\"T_bcb49_row2_col4\" class=\"data row2 col4\" ></td>\n",
       "      <td id=\"T_bcb49_row2_col5\" class=\"data row2 col5\" >2.59%</td>\n",
       "      <td id=\"T_bcb49_row2_col6\" class=\"data row2 col6\" >-2.30%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row3\" class=\"row_heading level0 row3\" >1.960000</th>\n",
       "      <td id=\"T_bcb49_row3_col0\" class=\"data row3 col0\" ></td>\n",
       "      <td id=\"T_bcb49_row3_col1\" class=\"data row3 col1\" ></td>\n",
       "      <td id=\"T_bcb49_row3_col2\" class=\"data row3 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row3_col3\" class=\"data row3 col3\" ></td>\n",
       "      <td id=\"T_bcb49_row3_col4\" class=\"data row3 col4\" >1.34%</td>\n",
       "      <td id=\"T_bcb49_row3_col5\" class=\"data row3 col5\" >-4.67%</td>\n",
       "      <td id=\"T_bcb49_row3_col6\" class=\"data row3 col6\" >-0.80%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row4\" class=\"row_heading level0 row4\" >2.740000</th>\n",
       "      <td id=\"T_bcb49_row4_col0\" class=\"data row4 col0\" ></td>\n",
       "      <td id=\"T_bcb49_row4_col1\" class=\"data row4 col1\" ></td>\n",
       "      <td id=\"T_bcb49_row4_col2\" class=\"data row4 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row4_col3\" class=\"data row4 col3\" >4.70%</td>\n",
       "      <td id=\"T_bcb49_row4_col4\" class=\"data row4 col4\" >-0.47%</td>\n",
       "      <td id=\"T_bcb49_row4_col5\" class=\"data row4 col5\" >0.55%</td>\n",
       "      <td id=\"T_bcb49_row4_col6\" class=\"data row4 col6\" >-0.76%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row5\" class=\"row_heading level0 row5\" >3.840000</th>\n",
       "      <td id=\"T_bcb49_row5_col0\" class=\"data row5 col0\" ></td>\n",
       "      <td id=\"T_bcb49_row5_col1\" class=\"data row5 col1\" ></td>\n",
       "      <td id=\"T_bcb49_row5_col2\" class=\"data row5 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row5_col3\" class=\"data row5 col3\" >-0.58%</td>\n",
       "      <td id=\"T_bcb49_row5_col4\" class=\"data row5 col4\" >-2.10%</td>\n",
       "      <td id=\"T_bcb49_row5_col5\" class=\"data row5 col5\" >-5.36%</td>\n",
       "      <td id=\"T_bcb49_row5_col6\" class=\"data row5 col6\" >0.98%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row6\" class=\"row_heading level0 row6\" >5.380000</th>\n",
       "      <td id=\"T_bcb49_row6_col0\" class=\"data row6 col0\" ></td>\n",
       "      <td id=\"T_bcb49_row6_col1\" class=\"data row6 col1\" >-1.04%</td>\n",
       "      <td id=\"T_bcb49_row6_col2\" class=\"data row6 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row6_col3\" class=\"data row6 col3\" >-1.03%</td>\n",
       "      <td id=\"T_bcb49_row6_col4\" class=\"data row6 col4\" >-2.18%</td>\n",
       "      <td id=\"T_bcb49_row6_col5\" class=\"data row6 col5\" >-1.97%</td>\n",
       "      <td id=\"T_bcb49_row6_col6\" class=\"data row6 col6\" >1.59%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row7\" class=\"row_heading level0 row7\" >7.530000</th>\n",
       "      <td id=\"T_bcb49_row7_col0\" class=\"data row7 col0\" >-1.41%</td>\n",
       "      <td id=\"T_bcb49_row7_col1\" class=\"data row7 col1\" >-1.46%</td>\n",
       "      <td id=\"T_bcb49_row7_col2\" class=\"data row7 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row7_col3\" class=\"data row7 col3\" >-0.33%</td>\n",
       "      <td id=\"T_bcb49_row7_col4\" class=\"data row7 col4\" >0.63%</td>\n",
       "      <td id=\"T_bcb49_row7_col5\" class=\"data row7 col5\" >-1.42%</td>\n",
       "      <td id=\"T_bcb49_row7_col6\" class=\"data row7 col6\" >4.01%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row8\" class=\"row_heading level0 row8\" >10.540000</th>\n",
       "      <td id=\"T_bcb49_row8_col0\" class=\"data row8 col0\" >-1.50%</td>\n",
       "      <td id=\"T_bcb49_row8_col1\" class=\"data row8 col1\" >-2.15%</td>\n",
       "      <td id=\"T_bcb49_row8_col2\" class=\"data row8 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row8_col3\" class=\"data row8 col3\" >3.80%</td>\n",
       "      <td id=\"T_bcb49_row8_col4\" class=\"data row8 col4\" >0.39%</td>\n",
       "      <td id=\"T_bcb49_row8_col5\" class=\"data row8 col5\" >1.36%</td>\n",
       "      <td id=\"T_bcb49_row8_col6\" class=\"data row8 col6\" >5.11%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row9\" class=\"row_heading level0 row9\" >14.760000</th>\n",
       "      <td id=\"T_bcb49_row9_col0\" class=\"data row9 col0\" >-1.93%</td>\n",
       "      <td id=\"T_bcb49_row9_col1\" class=\"data row9 col1\" >-0.81%</td>\n",
       "      <td id=\"T_bcb49_row9_col2\" class=\"data row9 col2\" >0.52%</td>\n",
       "      <td id=\"T_bcb49_row9_col3\" class=\"data row9 col3\" >2.84%</td>\n",
       "      <td id=\"T_bcb49_row9_col4\" class=\"data row9 col4\" >0.38%</td>\n",
       "      <td id=\"T_bcb49_row9_col5\" class=\"data row9 col5\" >1.68%</td>\n",
       "      <td id=\"T_bcb49_row9_col6\" class=\"data row9 col6\" >7.94%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row10\" class=\"row_heading level0 row10\" >20.660000</th>\n",
       "      <td id=\"T_bcb49_row10_col0\" class=\"data row10 col0\" >-2.52%</td>\n",
       "      <td id=\"T_bcb49_row10_col1\" class=\"data row10 col1\" >-1.77%</td>\n",
       "      <td id=\"T_bcb49_row10_col2\" class=\"data row10 col2\" >0.23%</td>\n",
       "      <td id=\"T_bcb49_row10_col3\" class=\"data row10 col3\" >-1.93%</td>\n",
       "      <td id=\"T_bcb49_row10_col4\" class=\"data row10 col4\" >2.61%</td>\n",
       "      <td id=\"T_bcb49_row10_col5\" class=\"data row10 col5\" >2.91%</td>\n",
       "      <td id=\"T_bcb49_row10_col6\" class=\"data row10 col6\" >8.59%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row11\" class=\"row_heading level0 row11\" >28.930000</th>\n",
       "      <td id=\"T_bcb49_row11_col0\" class=\"data row11 col0\" >-2.40%</td>\n",
       "      <td id=\"T_bcb49_row11_col1\" class=\"data row11 col1\" >0.85%</td>\n",
       "      <td id=\"T_bcb49_row11_col2\" class=\"data row11 col2\" >1.52%</td>\n",
       "      <td id=\"T_bcb49_row11_col3\" class=\"data row11 col3\" >4.23%</td>\n",
       "      <td id=\"T_bcb49_row11_col4\" class=\"data row11 col4\" >-0.39%</td>\n",
       "      <td id=\"T_bcb49_row11_col5\" class=\"data row11 col5\" >2.19%</td>\n",
       "      <td id=\"T_bcb49_row11_col6\" class=\"data row11 col6\" >6.20%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row12\" class=\"row_heading level0 row12\" >40.500000</th>\n",
       "      <td id=\"T_bcb49_row12_col0\" class=\"data row12 col0\" >-3.16%</td>\n",
       "      <td id=\"T_bcb49_row12_col1\" class=\"data row12 col1\" >-0.92%</td>\n",
       "      <td id=\"T_bcb49_row12_col2\" class=\"data row12 col2\" >-0.58%</td>\n",
       "      <td id=\"T_bcb49_row12_col3\" class=\"data row12 col3\" >5.40%</td>\n",
       "      <td id=\"T_bcb49_row12_col4\" class=\"data row12 col4\" >1.71%</td>\n",
       "      <td id=\"T_bcb49_row12_col5\" class=\"data row12 col5\" >0.75%</td>\n",
       "      <td id=\"T_bcb49_row12_col6\" class=\"data row12 col6\" >10.95%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row13\" class=\"row_heading level0 row13\" >56.690000</th>\n",
       "      <td id=\"T_bcb49_row13_col0\" class=\"data row13 col0\" >-1.70%</td>\n",
       "      <td id=\"T_bcb49_row13_col1\" class=\"data row13 col1\" >-1.47%</td>\n",
       "      <td id=\"T_bcb49_row13_col2\" class=\"data row13 col2\" >-1.01%</td>\n",
       "      <td id=\"T_bcb49_row13_col3\" class=\"data row13 col3\" >5.79%</td>\n",
       "      <td id=\"T_bcb49_row13_col4\" class=\"data row13 col4\" >-0.06%</td>\n",
       "      <td id=\"T_bcb49_row13_col5\" class=\"data row13 col5\" >-4.72%</td>\n",
       "      <td id=\"T_bcb49_row13_col6\" class=\"data row13 col6\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row14\" class=\"row_heading level0 row14\" >79.370000</th>\n",
       "      <td id=\"T_bcb49_row14_col0\" class=\"data row14 col0\" >-2.36%</td>\n",
       "      <td id=\"T_bcb49_row14_col1\" class=\"data row14 col1\" >-3.52%</td>\n",
       "      <td id=\"T_bcb49_row14_col2\" class=\"data row14 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row14_col3\" class=\"data row14 col3\" >2.76%</td>\n",
       "      <td id=\"T_bcb49_row14_col4\" class=\"data row14 col4\" >-2.11%</td>\n",
       "      <td id=\"T_bcb49_row14_col5\" class=\"data row14 col5\" ></td>\n",
       "      <td id=\"T_bcb49_row14_col6\" class=\"data row14 col6\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row15\" class=\"row_heading level0 row15\" >111.120000</th>\n",
       "      <td id=\"T_bcb49_row15_col0\" class=\"data row15 col0\" >-5.14%</td>\n",
       "      <td id=\"T_bcb49_row15_col1\" class=\"data row15 col1\" >-5.48%</td>\n",
       "      <td id=\"T_bcb49_row15_col2\" class=\"data row15 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row15_col3\" class=\"data row15 col3\" ></td>\n",
       "      <td id=\"T_bcb49_row15_col4\" class=\"data row15 col4\" ></td>\n",
       "      <td id=\"T_bcb49_row15_col5\" class=\"data row15 col5\" ></td>\n",
       "      <td id=\"T_bcb49_row15_col6\" class=\"data row15 col6\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bcb49_level0_row16\" class=\"row_heading level0 row16\" >155.570000</th>\n",
       "      <td id=\"T_bcb49_row16_col0\" class=\"data row16 col0\" ></td>\n",
       "      <td id=\"T_bcb49_row16_col1\" class=\"data row16 col1\" >-4.69%</td>\n",
       "      <td id=\"T_bcb49_row16_col2\" class=\"data row16 col2\" ></td>\n",
       "      <td id=\"T_bcb49_row16_col3\" class=\"data row16 col3\" ></td>\n",
       "      <td id=\"T_bcb49_row16_col4\" class=\"data row16 col4\" ></td>\n",
       "      <td id=\"T_bcb49_row16_col5\" class=\"data row16 col5\" ></td>\n",
       "      <td id=\"T_bcb49_row16_col6\" class=\"data row16 col6\" ></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x175e5d940>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B_W_Metric_raw = dataset[['difficulty', 'stability', 'p', 'y']].copy()\n",
    "B_W_Metric_raw['s_bin'] = B_W_Metric_raw['stability'].map(lambda x: round(math.pow(1.4, math.floor(math.log(x, 1.4))), 2))\n",
    "B_W_Metric_raw['d_bin'] = B_W_Metric_raw['difficulty'].map(lambda x: int(round(x)))\n",
    "B_W_Metric = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('mean').reset_index()\n",
    "B_W_Metric_count = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('count').reset_index()\n",
    "B_W_Metric['B-W'] = B_W_Metric['p'] - B_W_Metric['y']\n",
    "n = len(dataset)\n",
    "bins = len(B_W_Metric)\n",
    "B_W_Metric_pivot = B_W_Metric[B_W_Metric_count['p'] > max(50, n / (3 * bins))].pivot(index=\"s_bin\", columns='d_bin', values='B-W')\n",
    "B_W_Metric_pivot.apply(pd.to_numeric).style.background_gradient(cmap='seismic', axis=None, vmin=-0.2, vmax=0.2).format(\"{:.2%}\", na_rep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_Metric:  0.03967942303599237\n",
      "R-squared: -6.8749\n",
      "RMSE: 0.1527\n",
      "[0.68927589 0.25115013]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Universal Metric of FSRS: 0.0098\n",
      "Universal Metric of SM2: 0.0801\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sm2(history):\n",
    "    ivl = 0\n",
    "    ef = 2.5\n",
    "    reps = 0\n",
    "    for delta_t, rating in history:\n",
    "        delta_t = delta_t.item()\n",
    "        rating = rating.item() + 1\n",
    "        if rating > 2:\n",
    "            if reps == 0:\n",
    "                ivl = 1\n",
    "                reps = 1\n",
    "            elif reps == 1:\n",
    "                ivl = 6\n",
    "                reps = 2\n",
    "            else:\n",
    "                ivl = ivl * ef\n",
    "                reps += 1\n",
    "        else:\n",
    "            ivl = 1\n",
    "            reps = 0\n",
    "        ef = max(1.3, ef + (0.1 - (5 - rating) * (0.08 + (5 - rating) * 0.02)))\n",
    "        ivl = max(1, round(ivl+0.01))\n",
    "    return ivl\n",
    "\n",
    "dataset['sm2_interval'] = dataset['tensor'].map(sm2)\n",
    "dataset['sm2_p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['sm2_interval'])\n",
    "cross_comparison = dataset[['sm2_p', 'p', 'y']].copy()\n",
    "\n",
    "R_Metric = mean_squared_error(cross_comparison['y'], cross_comparison['sm2_p'], squared=False) - mean_squared_error(cross_comparison['y'], cross_comparison['p'], squared=False)\n",
    "print(\"R_Metric: \", R_Metric)\n",
    "plot_brier(dataset['sm2_p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(6, 6))\n",
    "\n",
    "cross_comparison['SM2_B-W'] = cross_comparison['sm2_p'] - cross_comparison['y']\n",
    "cross_comparison['SM2_bin'] = cross_comparison['sm2_p'].map(lambda x: round(x, 1))\n",
    "cross_comparison['FSRS_B-W'] = cross_comparison['p'] - cross_comparison['y']\n",
    "cross_comparison['FSRS_bin'] = cross_comparison['p'].map(lambda x: round(x, 1))\n",
    "\n",
    "plt.axhline(y = 0.0, color = 'black', linestyle = '-')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='SM2_bin').agg({'y': ['mean'], 'FSRS_B-W': ['mean'], 'p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of FSRS: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['p', 'mean'], sample_weight=cross_comparison_group['p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['p', 'percent'] = cross_comparison_group['p', 'count'] / cross_comparison_group['p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['FSRS_B-W', 'mean'], s=cross_comparison_group['p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['FSRS_B-W', 'mean'], label='FSRS by SM2')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='FSRS_bin').agg({'y': ['mean'], 'SM2_B-W': ['mean'], 'sm2_p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of SM2: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['sm2_p', 'mean'], sample_weight=cross_comparison_group['sm2_p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['sm2_p', 'percent'] = cross_comparison_group['sm2_p', 'count'] / cross_comparison_group['sm2_p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['SM2_B-W', 'mean'], s=cross_comparison_group['sm2_p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['SM2_B-W', 'mean'], label='SM2 by FSRS')\n",
    "\n",
    "plt.legend(loc='lower center')\n",
    "plt.grid(linestyle='--')\n",
    "plt.title(\"SM2 vs. FSRS\")\n",
    "plt.xlabel('Predicted R')\n",
    "plt.ylabel('B-W Metric')\n",
    "plt.xlim(0, 1)\n",
    "plt.xticks(np.arange(0, 1.1, 0.1))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsrs4anki",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
